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Committee on Physical Activity and Physical Education in the School Environment; Food and Nutrition Board; Institute of Medicine; Kohl HW III, Cook HD, editors. Educating the Student Body: Taking Physical Activity and Physical Education to School. Washington (DC): National Academies Press (US); 2013 Oct 30.

Cover of Educating the Student Body

Educating the Student Body: Taking Physical Activity and Physical Education to School.

  • Hardcopy Version at National Academies Press

4 Physical Activity, Fitness, and Physical Education: Effects on Academic Performance

Key messages.

  • Evidence suggests that increasing physical activity and physical fitness may improve academic performance and that time in the school day dedicated to recess, physical education class, and physical activity in the classroom may also facilitate academic performance.
  • Available evidence suggests that mathematics and reading are the academic topics that are most influenced by physical activity. These topics depend on efficient and effective executive function, which has been linked to physical activity and physical fitness.
  • Executive function and brain health underlie academic performance. Basic cognitive functions related to attention and memory facilitate learning, and these functions are enhanced by physical activity and higher aerobic fitness.
  • Single sessions of and long-term participation in physical activity improve cognitive performance and brain health. Children who participate in vigorous- or moderate-intensity physical activity benefit the most.
  • Given the importance of time on task to learning, students should be provided with frequent physical activity breaks that are developmentally appropriate.
  • Although presently understudied, physically active lessons offered in the classroom may increase time on task and attention to task in the classroom setting.

Although academic performance stems from a complex interaction between intellect and contextual variables, health is a vital moderating factor in a child's ability to learn. The idea that healthy children learn better is empirically supported and well accepted ( Basch, 2010 ), and multiple studies have confirmed that health benefits are associated with physical activity, including cardiovascular and muscular fitness, bone health, psychosocial outcomes, and cognitive and brain health ( Strong et al., 2005 ; see Chapter 3 ). The relationship of physical activity and physical fitness to cognitive and brain health and to academic performance is the subject of this chapter.

Given that the brain is responsible for both mental processes and physical actions of the human body, brain health is important across the life span. In adults, brain health, representing absence of disease and optimal structure and function, is measured in terms of quality of life and effective functioning in activities of daily living. In children, brain health can be measured in terms of successful development of attention, on-task behavior, memory, and academic performance in an educational setting. This chapter reviews the findings of recent research regarding the contribution of engagement in physical activity and the attainment of a health-enhancing level of physical fitness to cognitive and brain health in children. Correlational research examining the relationship among academic performance, physical fitness, and physical activity also is described. Because research in older adults has served as a model for understanding the effects of physical activity and fitness on the developing brain during childhood, the adult research is briefly discussed. The short- and long-term cognitive benefits of both a single session of and regular participation in physical activity are summarized.

Before outlining the health benefits of physical activity and fitness, it is important to note that many factors influence academic performance. Among these are socioeconomic status ( Sirin, 2005 ), parental involvement ( Fan and Chen, 2001 ), and a host of other demographic factors. A valuable predictor of student academic performance is a parent having clear expectations for the child's academic success. Attendance is another factor confirmed as having a significant impact on academic performance ( Stanca, 2006 ; Baxter et al., 2011 ). Because children must be present to learn the desired content, attendance should be measured in considering factors related to academic performance.

  • PHYSICAL FITNESS AND PHYSICAL ACTIVITY: RELATION TO ACADEMIC PERFORMANCE

State-mandated academic achievement testing has had the unintended consequence of reducing opportunities for children to be physically active during the school day and beyond. In addition to a general shifting of time in school away from physical education to allow for more time on academic subjects, some children are withheld from physical education classes or recess to participate in remedial or enriched learning experiences designed to increase academic performance ( Pellegrini and Bohn, 2005 ; see Chapter 5 ). Yet little evidence supports the notion that more time allocated to subject matter will translate into better test scores. Indeed, 11 of 14 correlational studies of physical activity during the school day demonstrate a positive relationship to academic performance ( Rasberry et al., 2011 ). Overall, a rapidly growing body of work suggests that time spent engaged in physical activity is related not only to a healthier body but also to a healthier mind ( Hillman et al., 2008 ).

Children respond faster and with greater accuracy to a variety of cognitive tasks after participating in a session of physical activity ( Tomporowski, 2003 ; Budde et al., 2008 ; Hillman et al., 2009 ; Pesce et al., 2009 ; Ellemberg and St-Louis-Deschênes, 2010 ). A single bout of moderate-intensity physical activity has been found to increase neural and behavioral concomitants associated with the allocation of attention to a specific cognitive task ( Hillman et al., 2009 ; Pontifex et al., 2012 ). And when children who participated in 30 minutes of aerobic physical activity were compared with children who watched television for the same amount of time, the former children cognitively outperformed the latter ( Ellemberg and St-Louis-Desêhenes, 2010 ). Visual task switching data among 69 overweight and inactive children did not show differences between cognitive performance after treadmill walking and sitting ( Tomporowski et al., 2008b ).

When physical activity is used as a break from academic learning time, postengagement effects include better attention ( Grieco et al., 2009 ; Bartholomew and Jowers, 2011 ), increased on-task behaviors ( Mahar et al., 2006 ), and improved academic performance ( Donnelly and Lambourne, 2011 ). Comparisons between 1st-grade students housed in a classroom with stand-sit desks where the child could stand at his/her discretion and in classrooms containing traditional furniture showed that the former children were highly likely to stand, thus expending significantly more energy than those who were seated ( Benden et al., 2011 ). More important, teachers can offer physical activity breaks as part of a supplemental curriculum or simply as a way to reset student attention during a lesson ( Kibbe et al., 2011 ; see Chapter 6 ) and when provided with minimal training can efficaciously produce vigorous or moderate energy expenditure in students ( Stewart et al., 2004 ). Further, after-school physical activity programs have demonstrated the ability to improve cardiovascular endurance, and this increase in aerobic fitness has been shown to mediate improvements in academic performance ( Fredericks et al., 2006 ), as well as the allocation of neural resources underlying performance on a working memory task ( Kamijo et al., 2011 ).

Over the past three decades, several reviews and meta-analyses have described the relationship among physical fitness, physical activity, and cognition (broadly defined as all mental processes). The majority of these reviews have focused on the relationship between academic performance and physical fitness—a physiological trait commonly defined in terms of cardiorespiratory capacity (e.g., maximal oxygen consumption; see Chapter 3 ). More recently, reviews have attempted to describe the effects of an acute or single bout of physical activity, as a behavior, on academic performance. These reviews have focused on brain health in older adults ( Colcombe and Kramer, 2003 ), as well as the effects of acute physical activity on cognition in adults ( Tomporowski, 2003 ). Some have considered age as part of the analysis ( Etnier et al., 1997 , 2006 ). Reviews focusing on research conducted in children ( Sibley and Etnier, 2003 ) have examined the relationship among physical activity, participation in sports, and academic performance ( Trudeau and Shephard, 2008 , 2010 ; Singh et al., 2012 ); physical activity and mental and cognitive health ( Biddle and Asare, 2011 ); and physical activity, nutrition, and academic performance ( Burkhalter and Hillman, 2011 ). The findings of most of these reviews align with the conclusions presented in a meta-analytic review conducted by Fedewa and Ahn (2011) . The studies reviewed by Fedewa and Ahn include experimental/quasi-experimental as well as cross-sectional and correlational designs, with the experimental designs yielding the highest effect sizes. The strongest relationships were found between aerobic fitness and achievement in mathematics, followed by IQ and reading performance. The range of cognitive performance measures, participant characteristics, and types of research design all mediated the relationship among physical activity, fitness, and academic performance. With regard to physical activity interventions, which were carried out both within and beyond the school day, those involving small groups of peers (around 10 youth of a similar age) were associated with the greatest gains in academic performance.

The number of peer-reviewed publications on this topic is growing exponentially. Further evidence of the growth of this line of inquiry is its increased global presence. Positive relationships among physical activity, physical fitness, and academic performance have been found among students from the Netherlands ( Singh et al., 2012 ) and Taiwan ( Chih and Chen, 2011 ). Broadly speaking, however, many of these studies show small to moderate effects and suffer from poor research designs ( Biddle and Asare, 2011 ; Singh et al., 2012 ).

Basch (2010) conducted a comprehensive review of how children's health and health disparities influence academic performance and learning. The author's report draws on empirical evidence suggesting that education reform will be ineffective unless children's health is made a priority. Basch concludes that schools may be the only place where health inequities can be addressed and that, if children's basic health needs are not met, they will struggle to learn regardless of the effectiveness of the instructional materials used. More recently, Efrat (2011) conducted a review of physical activity, fitness, and academic performance to examine the achievement gap. He discovered that only seven studies had included socioeconomic status as a variable, despite its known relationship to education ( Sirin, 2005 ).

Physical Fitness as a Learning Outcome of Physical Education and Its Relation to Academic Performance

Achieving and maintaining a healthy level of aerobic fitness, as defined using criterion-referenced standards from the National Health and Nutrition Examination Survey (NHANES; Welk et al., 2011 ), is a desired learning outcome of physical education programming. Regular participation in physical activity also is a national learning standard for physical education, a standard intended to facilitate the establishment of habitual and meaningful engagement in physical activity ( NASPE, 2004 ). Yet although physical fitness and participation in physical activity are established as learning outcomes in all 50 states, there is little evidence to suggest that children actually achieve and maintain these standards (see Chapter 2 ).

Statewide and national datasets containing data on youth physical fitness and academic performance have increased access to student-level data on this subject ( Grissom, 2005 ; Cottrell et al., 2007 ; Carlson et al., 2008 ; Chomitz et al., 2008 ; Wittberg et al., 2010 ; Van Dusen et al., 2011 ). Early research in South Australia focused on quantifying the benefits of physical activity and physical education during the school day; the benefits noted included increased physical fitness, decreased body fat, and reduced risk for cardiovascular disease ( Dwyer et al., 1979 , 1983 ). Even today, Dwyer and colleagues are among the few scholars who regularly include in their research measures of physical activity intensity in the school environment, which is believed to be a key reason why they are able to report differentiated effects of different intensities. A longitudinal study in Trois-Rivières, Québec, Canada, tracked how the academic performance of children from grades 1 through 6 was related to student health, motor skills, and time spent in physical education. The researchers concluded that additional time dedicated to physical education did not inhibit academic performance ( Shephard et al., 1984 ; Shephard, 1986 ; Trudeau and Shephard, 2008 ).

Longitudinal follow-up investigating the long-term benefits of enhanced physical education experiences is encouraging but largely inconclusive. In a study examining the effects of daily physical education during elementary school on physical activity during adulthood, 720 men and women completed the Québec Health Survey ( Trudeau et al., 1999 ). Findings suggest that physical education was associated with physical activity in later life for females but not males ( Trudeau et al., 1999 ); most of the associations were significant but weak ( Trudeau et al., 2004 ). Adult body mass index (BMI) at age 34 was related to childhood BMI at ages 10-12 in females but not males ( Trudeau et al., 2001 ). Longitudinal studies such as those conducted in Sweden and Finland also suggest that physical education experiences may be related to adult engagement in physical activity ( Glenmark, 1994 ; Telama et al., 1997 ). From an academic performance perspective, longitudinal data on men who enlisted for military service imply that cardiovascular fitness at age 18 predicted cognitive performance in later life (Aberg et al., 2009), thereby supporting the idea of offering physical education and physical activity opportunities well into emerging adulthood through secondary and postsecondary education.

Castelli and colleagues (2007) investigated younger children (in 3rd and 5th grades) and the differential contributions of the various subcomponents of the Fitnessgram ® . Specifically, they examined the individual contributions of aerobic capacity, muscle strength, muscle flexibility, and body composition to performance in mathematics and reading on the Illinois Standardized Achievement Test among a sample of 259 children. Their findings corroborate those of the California Department of Education ( Grissom, 2005 ), indicating a general relationship between fitness and achievement test performance. When the individual components of the Fitnessgram were decomposed, the researchers determined that only aerobic capacity was related to test performance. Muscle strength and flexibility showed no relationship, while an inverse association of BMI with test performance was observed, such that higher BMI was associated with lower test performance. Although Baxter and colleagues (2011) confirmed the importance of attending school in relation to academic performance through the use of 4th-grade student recall, correlations with BMI were not significant.

State-mandated implementation of the coordinated school health model requires all schools in Texas to conduct annual fitness testing using the Fitnessgram among students in grades 3-12. In a special issue of Research Quarterly for Exercise and Sport (2010), multiple articles describe the current state of physical fitness among children in Texas; confirm the associations among school performance levels, academic achievement, and physical fitness ( Welk et al., 2010 ; Zhu et al., 2010 ); and demonstrate the ability of qualified physical education teachers to administer physical fitness tests ( Zhu et al., 2010 ). Also using data from Texas schools, Van Dusen and colleagues (2011) found that cardiovascular fitness had the strongest association with academic performance, particularly in mathematics over reading. Unlike previous research, which demonstrated a steady decline in fitness by developmental stage ( Duncan et al., 2007 ), this study found that cardiovascular fitness did decrease but not significantly ( Van Dusen et al., 2011 ). Aerobic fitness, then, may be important to academic performance, as there may be a dose-response relationship ( Van Dusen et al., 2011 ).

Using a large sample of students in grades 4-8, Chomitz and colleagues (2008) found that the likelihood of passing both mathematics and English achievement tests increased with the number of fitness tests passed during physical education class, and the odds of passing the mathematics achievement tests were inversely related to higher body weight. Similar to the findings of Castelli and colleagues (2007) , socioeconomic status and demographic factors explained little of the relationship between aerobic fitness and academic performance; however, socioeconomic status may be an explanatory variable for students of low fitness ( London and Castrechini, 2011 ).

In sum, numerous cross-sectional and correlational studies demonstrate small-to-moderate positive or null associations between physical fitness ( Grissom, 2005 ; Cottrell et al., 2007 ; Edwards et al., 2009; Eveland-Sayers et al., 2009 ; Cooper et al., 2010 ; Welk et al., 2010 ; Wittberg et al., 2010 ; Zhu et al., 2010 ; Van Dusen et al., 2011 ), particularly aerobic fitness, and academic performance ( Castelli et al, 2007 ; Chomitz et al., 2008 ; Roberts et al., 2010 ; Welk et al., 2010 ; Chih and Chen, 2011 ; London and Castrechini, 2011 ; Van Dusen et al., 2011 ). Moreover, the findings may support a dose-response association, suggesting that the more components of physical fitness (e.g., cardiovascular endurance, strength, muscle endurance) considered acceptable for the specific age and gender that are present, the greater the likelihood of successful academic performance. From a public health and policy standpoint, the conclusions these findings support are limited by few causal inferences, a lack of data confirmation, and inadequate reliability because the data were often collected by nonresearchers or through self-report methods. It may also be noted that this research includes no known longitudinal studies and few randomized controlled trials (examples are included later in this chapter in the discussion of the developing brain).

Physical Activity, Physical Education, and Academic Performance

In contrast with the correlational data presented above for physical fitness, more information is needed on the direct effects of participation in physical activity programming and physical education classes on academic performance.

In a meta-analysis, Sibley and Etnier (2003) found a positive relationship between physical activity and cognition in school-age youth (aged 4-18), suggesting that physical activity, as well as physical fitness, may be related to cognitive outcomes during development. Participation in physical activity was related to cognitive performance in eight measurement categories (perceptual skills, IQ, achievement, verbal tests, mathematics tests, memory, developmental level/academic readiness, and “other”), with results indicating a beneficial relationship of physical activity to all cognitive outcomes except memory ( Sibley and Etnier, 2003 ). Since that meta-analysis, however, several papers have reported robust relationships between aerobic fitness and different aspects of memory in children (e.g., Chaddock et al., 2010a , 2011 ; Kamijo et al., 2011 ; Monti et al., 2012 ). Regardless, the comprehensive review of Sibley and Etnier (2003) was important because it helped bring attention to an emerging literature suggesting that physical activity may benefit cognitive development even as it also demonstrated the need for further study to better understand the multifaceted relationship between physical activity and cognitive and brain health.

The regular engagement in physical activity achieved during physical education programming can also be related to academic performance, especially when the class is taught by a physical education teacher. The Sports, Play, and Active Recreation for Kids (SPARK) study examined the effects of a 2-year health-related physical education program on academic performance in children ( Sallis et al., 1999 ). In an experimental design, seven elementary schools were randomly assigned to one of three conditions: (1) a specialist condition in which certified physical education teachers delivered the SPARK curriculum, (2) a trained-teacher condition in which classroom teachers implemented the curriculum, and (3) a control condition in which classroom teachers implemented the local physical education curriculum. No significant differences by condition were found for mathematics testing; however, reading scores were significantly higher in the specialist condition relative to the control condition ( Sallis et al., 1999 ), while language scores were significantly lower in the specialist condition than in the other two conditions. The authors conclude that spending time in physical education with a specialist did not have a negative effect on academic performance. Shortcomings of this research include the amount of data loss from pre- to posttest, the use of results of 2nd-grade testing that exceeded the national average in performance as baseline data, and the use of norm-referenced rather than criterion-based testing.

In seminal research conducted by Gabbard and Barton (1979) , six different conditions of physical activity (no activity; 20, 30, 40, and 50 minutes; and posttest no activity) were completed by 106 2nd graders during physical education. Each physical activity session was followed by 5 minutes of rest and the completion of 36 math problems. The authors found a potential threshold effect whereby only the 50-minute condition improved mathematical performance, with no differences by gender.

A longitudinal study of the kindergarten class of 1998–1999, using data from the Early Childhood Longitudinal Study, investigated the association between enrollment in physical education and academic achievement ( Carlson et al., 2008 ). Higher amounts of physical education were correlated with better academic performance in mathematics among females, but this finding did not hold true for males.

Ahamed and colleagues (2007) found in a cluster randomized trial that, after 16 months of a classroom-based physical activity intervention, there was no significant difference between the treatment and control groups in performance on the standardized Cognitive Abilities Test, Third Edition (CAT-3). Others have found, however, that coordinative exercise ( Budde et al., 2008 ) or bouts of vigorous physical activity during free time ( Coe et al., 2006 ) contribute to higher levels of academic performance. Specifically, Coe and colleagues examined the association of enrollment in physical education and self-reported vigorous- or moderate-intensity physical activity outside school with performance in core academic courses and on the Terra Nova Standardized Achievement Test among more than 200 6th-grade students. Their findings indicate that academic performance was unaffected by enrollment in physical education classes, which were found to average only 19 minutes of vigorous- or moderate-intensity physical activity. When time spent engaged in vigorous- or moderate-intensity physical activity outside of school was considered, however, a significant positive relation to academic performance emerged, with more time engaged in vigorous- or moderate-intensity physical activity being related to better grades but not test scores ( Coe et al., 2006 ).

Studies of participation in sports and academic achievement have found positive associations ( Mechanic and Hansell, 1987 ; Dexter, 1999 ; Crosnoe, 2002 ; Eitle and Eitle, 2002 ; Stephens and Schaben, 2002 ; Eitle, 2005 ; Miller et al., 2005 ; Fox et al., 2010 ; Ruiz et al., 2010 ); higher grade point averages (GPAs) in season than out of season ( Silliker and Quirk, 1997 ); a negative association between cheerleading and science performance ( Hanson and Kraus, 1998 ); and weak and negative associations between the amount of time spent participating in sports and performance in English-language class among 13-, 14-, and 16-year-old students ( Daley and Ryan, 2000 ). Other studies, however, have found no association between participation in sports and academic performance ( Fisher et al., 1996 ). The findings of these studies need to be interpreted with caution as many of their designs failed to account for the level of participation by individuals in the sport (e.g., amount of playing time, type and intensity of physical activity engagement by sport). Further, it is unclear whether policies required students to have higher GPAs to be eligible for participation. Offering sports opportunities is well justified regardless of the cognitive benefits, however, given that adolescents may be less likely to engage in risky behaviors when involved in sports or other extracurricular activities ( Page et al., 1998 ; Elder et al., 2000 ; Taliaferro et al., 2010 ), that participation in sports increases physical fitness, and that affiliation with sports enhances school connectedness.

Although a consensus on the relationship of physical activity to academic achievement has not been reached, the vast majority of available evidence suggests the relationship is either positive or neutral. The meta-analytic review by Fedewa and Ahn (2011) suggests that interventions entailing aerobic physical activity have the greatest impact on academic performance; however, all types of physical activity, except those involving flexibility alone, contribute to enhanced academic performance, as do interventions that use small groups (about 10 students) rather than individuals or large groups. Regardless of the strength of the findings, the literature indicates that time spent engaged in physical activity is beneficial to children because it has not been found to detract from academic performance, and in fact can improve overall health and function ( Sallis et al., 1999 ; Hillman et al., 2008 ; Tomporowski et al., 2008a ; Trudeau and Shephard, 2008 ; Rasberry et al., 2011 ).

Single Bouts of Physical Activity

Beyond formal physical education, evidence suggests that multi-component approaches are a viable means of providing physical activity opportunities for children across the school curriculum (see also Chapter 6 ). Although health-related fitness lessons taught by certified physical education teachers result in greater student fitness gains relative to such lessons taught by other teachers ( Sallis et al., 1999 ), non-physical education teachers are capable of providing opportunities to be physically active within the classroom ( Kibbe et al., 2011 ). Single sessions or bouts of physical activity have independent merit, offering immediate benefits that can enhance the learning experience. Studies have found that single bouts of physical activity result in improved attention ( Hillman et al., 2003 , 2009 ; Pontifex et al., 2012 ), better working memory ( Pontifex et al., 2009 ), and increased academic learning time and reduced off-task behaviors ( Mahar et al., 2006 ; Bartholomew and Jowers, 2011 ). Yet single bouts of physical activity have differential effects, as very vigorous exercise has been associated with cognitive fatigue and even cognitive decline in adults ( Tomporowski, 2003 ). As seen in Figure 4-1 , high levels of effort, arousal, or activation can influence perception, decision making, response preparation, and actual response. For discussion of the underlying constructs and differential effects of single bouts of physical activity on cognitive performance, see Tomporowski (2003) .

Information processing: Diagram of a simplified version of Sanders's (1983) cognitive-energetic model of human information processing (adapted from Jones and Hardy, 1989). SOURCE: Tomporowski, 2003. Reprinted with permission.

For children, classrooms are busy places where they must distinguish relevant information from distractions that emerge from many different sources occurring simultaneously. A student must listen to the teacher, adhere to classroom procedures, focus on a specific task, hold and retain information, and make connections between novel information and previous experiences. Hillman and colleagues (2009) demonstrated that a single bout of moderate-intensity walking (60 percent of maximum heart rate) resulted in significant improvements in performance on a task requiring attentional inhibition (e.g., the ability to focus on a single task). These findings were accompanied by changes in neuroelectric measures underlying the allocation of attention (see Figure 4-2 ) and significant improvements on the reading subtest of the Wide Range Achievement Test. No such effects were observed following a similar duration of quiet rest. These findings were later replicated and extended to demonstrate benefits for both mathematics and reading performance in healthy children and those diagnosed with attention deficit hyperactivity disorder ( Pontifex et al., 2013 ). Further replications of these findings demonstrated that a single bout of moderate-intensity exercise using a treadmill improved performance on a task of attention and inhibition, but similar benefits were not derived from moderate-intensity exercise that involved exergaming ( O'Leary et al., 2011 ). It was also found that such benefits were derived following cessation of, but not during, the bout of exercise ( Drollette et al., 2012 ). The applications of such empirical findings within the school setting remain unclear.

Effects of a single session of exercise in preadolescent children. SOURCE: Hillman et al., 2009. Reprinted with permission.

A randomized controlled trial entitled Physical Activity Across the Curriculum (PAAC) used cluster randomization among 24 schools to examine the effects of physically active classroom lessons on BMI and academic achievement ( Donnelly et al., 2009 ). The academically oriented physical activities were intended to be of vigorous or moderate intensity (3–6 metabolic equivalents [METs]) and to last approximately 10 minutes and were specifically designed to supplement content in mathematics, language arts, geography, history, spelling, science, and health. The study followed 665 boys and 677 girls for 3 years as they rose from 2nd or 3rd to 4th or 5th grades. Changes in academic achievement, fitness, and blood screening were considered secondary outcomes. During a 3-year period, students who engaged in physically active lessons, on average, improved their academic achievement by 6 percent, while the control groups exhibited a 1 percent decrease. In students who experienced at least 75 minutes of PAAC lessons per week, BMI remained stable (see Figure 4-3 ).

Change in academic scores from baseline after physically active classroom lessons in elementary schools in northeast Kansas (2003–2006). NOTE: All differences between the Physical Activity Across the Curriculum (PAAC) group ( N = 117) and control (more...)

It is important to note that cognitive tasks completed before, during, and after physical activity show varying effects, but the effects were always positive compared with sedentary behavior. In a study carried out by Drollette and colleagues (2012) , 36 preadolescent children completed two cognitive tasks—a flanker task to assess attention and inhibition and a spatial nback task to assess working memory—before, during, and after seated rest and treadmill walking conditions. The children sat or walked on different days for an average of 19 minutes. The results suggest that the physical activity enhanced cognitive performance for the attention task but not for the task requiring working memory. Accordingly, although more research is needed, the authors suggest that the acute effects of exercise may be selective to certain cognitive processes (i.e., attentional inhibition) while unrelated to others (e.g., working memory). Indeed, data collected using a task-switching paradigm (i.e., a task designed to assess multitasking and requiring the scheduling of attention to multiple aspects of the environment) among 69 overweight and inactive children did not show differences in cognitive performance following acute bouts of treadmill walking or sitting ( Tomporowski et al., 2008b ). Thus, findings to date indicate a robust relationship of acute exercise to transient improvements in attention but appear inconsistent for other aspects of cognition.

Academic Learning Time and On- and Off-Task Behaviors

Excessive time on task, inattention to task, off-task behavior, and delinquency are important considerations in the learning environment given the importance of academic learning time to academic performance. These behaviors are observable and of concern to teachers as they detract from the learning environment. Systematic observation by trained observers may yield important insight regarding the effects of short physical activity breaks on these behaviors. Indeed, systematic observations of student behavior have been used as an alternative means of measuring academic performance ( Mahar et al., 2006 ; Grieco et al., 2009 ).

After the development of classroom-based physical activities, called Energizers, teachers were trained in how to implement such activities in their lessons at least twice per week ( Mahar et al., 2006 ). Measurements of baseline physical activity and on-task behaviors were collected in two 3rd-grade and two 4th-grade classes, using pedometers and direct observation. The intervention included 243 students, while 108 served as controls by not engaging in the activities. A subgroup of 62 3rd and 4th graders was observed for on-task behavior in the classroom following the physical activity. Children who participated in Energizers took more steps during the school day than those who did not; they also increased their on-task behaviors by more than 20 percent over baseline measures.

A systematic review of a similar in-class, academically oriented, physical activity plan—Take 10!—was conducted to identify the effects of its implementation after it had been in use for 10 years ( Kibbe et al., 2011 ). The findings suggest that children who experienced Take 10! in the classroom engaged in moderate to vigorous physical activity (6.16 to 6.42 METs) and had lower BMIs than those who did not. Further, children in the Take 10! classrooms had better fluid intelligence ( Reed et al., 2010 ) and higher academic achievement scores ( Donnelly et al., 2009 ).

Some have expressed concern that introducing physical activity into the classroom setting may be distracting to students. Yet in one study it was sedentary students who demonstrated a decrease in time on task, while active students returned to the same level of on-task behavior after an active learning task ( Grieco et al., 2009 ). Among the 97 3rd-grade students in this study, a small but nonsignificant increase in on-task behaviors was seen immediately following these active lessons. Additionally, these improvements were not mediated by BMI.

In sum, although presently understudied, physically active lessons may increase time on task and attention to task in the classroom setting. Given the complexity of the typical classroom, the strategy of including content-specific lessons that incorporate physical activity may be justified.

It is recommended that every child have 20 minutes of recess each day and that this time be outdoors whenever possible, in a safe activity ( NASPE, 2006 ). Consistent engagement in recess can help students refine social skills, learn social mediation skills surrounding fair play, obtain additional minutes of vigorous- or moderate-intensity physical activity that contribute toward the recommend 60 minutes or more per day, and have an opportunity to express their imagination through free play ( Pellegrini and Bohn, 2005 ; see also Chapter 6 ). When children participate in recess before lunch, additional benefits accrue, such as less food waste, increased incidence of appropriate behavior in the cafeteria during lunch, and greater student readiness to learn upon returning to the classroom after lunch ( Getlinger et al., 1996 ; Wechsler et al., 2001 ).

To examine the effects of engagement in physical activity during recess on classroom behavior, Barros and colleagues (2009) examined data from the Early Childhood Longitudinal Study on 10,000 8- to 9-year-old children. Teachers provided the number of minutes of recess as well as a ranking of classroom behavior (ranging from “misbehaves frequently” to “behaves exceptionally well”). Results indicate that children who had at least 15 minutes of recess were more likely to exhibit appropriate behavior in the classroom ( Barros et al., 2009 ). In another study, 43 4th-grade students were randomly assigned to 1 or no days of recess to examine the effects on classroom behavior ( Jarrett et al., 1998 ). The researchers concluded that on-task behavior was better among the children who had recess. A moderate effect size (= 0.51) was observed. In a series of studies examining kindergartners' attention to task following a 20-minute recess, increased time on task was observed during learning centers and story reading ( Pellegrini et al., 1995 ). Despite these positive findings centered on improved attention, it is important to note that few of these studies actually measured the intensity of the physical activity during recess.

From a slightly different perspective, survey data from 547 Virginia elementary school principals suggest that time dedicated to student participation in physical education, art, and music did not negatively influence academic performance ( Wilkins et al., 2003 ). Thus, the strategy of reducing time spent in physical education to increase academic performance may not have the desired effect. The evidence on in-school physical activity supports the provision of physical activity breaks during the school day as a way to increase fluid intelligence, time on task, and attention. However, it remains unclear what portion of these effects can be attributed to a break from academic time and what portion is a direct result of the specific demands/characteristics of the physical activity.

  • THE DEVELOPING bRAIN, PHYSICAL ACTIVITY, AND BRAIN HEALTH

The study of brain health has grown beyond simply measuring behavioral outcomes such as task performance and reaction time (e.g., cognitive processing speed). New technology has emerged that has allowed scientists to understand the impact of lifestyle factors on the brain from the body systems level down to the molecular level. A greater understanding of the cognitive components that subserve academic performance and may be amenable to intervention has thereby been gained. Research conducted in both laboratory and field settings has helped define this line of inquiry and identify some preliminary underlying mechanisms.

The Evidence Base on the Relationship of Physical Activity to Brain Health and Cognition in Older Adults

Despite the current focus on the relationship of physical activity to cognitive development, the evidence base is larger on the association of physical activity with brain health and cognition during aging. Much can be learned about how physical activity affects childhood cognition and scholastic achievement through this work. Despite earlier investigations into the relationship of physical activity to cognitive aging (see Etnier et al., 1997 , for a review), the field was shaped by the findings of Kramer and colleagues (1999) , who examined the effects of aerobic fitness training on older adults using a randomized controlled design. Specifically, 124 older adults aged 60 and 75 were randomly assigned to a 6-month intervention of either walking (i.e., aerobic training) or flexibility (i.e., nonaerobic) training. The walking group but not the flexibility group showed improved cognitive performance, measured as a shorter response time to the presented stimulus. Results from a series of tasks that tapped different aspects of cognitive control indicated that engagement in physical activity is a beneficial means of combating cognitive aging ( Kramer et al., 1999 ).

Cognitive control, or executive control, is involved in the selection, scheduling, and coordination of computational processes underlying perception, memory, and goal-directed action. These processes allow for the optimization of behavioral interactions within the environment through flexible modulation of the ability to control attention ( MacDonald et al., 2000 ; Botvinick et al., 2001 ). Core cognitive processes that make up cognitive control or executive control include inhibition, working memory, and cognitive flexibility ( Diamond, 2006 ), processes mediated by networks that involve the prefrontal cortex. Inhibition (or inhibitory control) refers to the ability to override a strong internal or external pull so as to act appropriately within the demands imposed by the environment ( Davidson et al., 2006 ). For example, one exerts inhibitory control when one stops speaking when the teacher begins lecturing. Working memory refers to the ability to represent information mentally, manipulate stored information, and act on the information ( Davidson et al., 2006 ). In solving a difficult mathematical problem, for example, one must often remember the remainder. Finally, cognitive flexibility refers to the ability to switch perspectives, focus attention, and adapt behavior quickly and flexibly for the purposes of goal-directed action ( Blair et al., 2005 ; Davidson et al., 2006 ; Diamond, 2006 ). For example, one must shift attention from the teacher who is teaching a lesson to one's notes to write down information for later study.

Based on their earlier findings on changes in cognitive control induced by aerobic training, Colcombe and Kramer (2003) conducted a meta-analysis to examine the relationship between aerobic training and cognition in older adults aged 55-80 using data from 18 randomized controlled exercise interventions. Their findings suggest that aerobic training is associated with general cognitive benefits that are selectively and disproportionately greater for tasks or task components requiring greater amounts of cognitive control. A second and more recent meta-analysis ( Smith et al., 2010 ) corroborates the findings of Colcombe and Kramer, indicating that aerobic exercise is related to attention, processing speed, memory, and cognitive control; however, it should be noted that smaller effect sizes were observed, likely a result of the studies included in the respective meta-analyses. In older adults, then, aerobic training selectively improves cognition.

Hillman and colleagues (2006) examined the relationship between physical activity and inhibition (one aspect of cognitive control) using a computer-based stimulus-response protocol in 241 individuals aged 15-71. Their results indicate that greater amounts of physical activity are related to decreased response speed across task conditions requiring variable amounts of inhibition, suggesting a generalized relationship between physical activity and response speed. In addition, the authors found physical activity to be related to better accuracy across conditions in older adults, while no such relationship was observed for younger adults. Of interest, this relationship was disproportionately larger for the condition requiring greater amounts of inhibition in the older adults, suggesting that physical activity has both a general and selective association with task performance ( Hillman et al., 2006 ).

With advances in neuroimaging techniques, understanding of the effects of physical activity and aerobic fitness on brain structure and function has advanced rapidly over the past decade. In particular, a series of studies ( Colcombe et al., 2003 , 2004 , 2006 ; Kramer and Erickson, 2007 ; Hillman et al., 2008 ) of older individuals has been conducted to elucidate the relation of aerobic fitness to the brain and cognition. Normal aging results in the loss of brain tissue ( Colcombe et al., 2003 ), with markedly larger loss evidenced in the frontal, temporal, and parietal regions ( Raz, 2000 ). Thus cognitive functions subserved by these brain regions (such as those involved in cognitive control and aspects of memory) are expected to decay more dramatically than other aspects of cognition.

Colcombe and colleagues (2003) investigated the relationship of aerobic fitness to gray and white matter tissue loss using magnetic resonance imaging (MRI) in 55 healthy older adults aged 55-79. They observed robust age-related decreases in tissue density in the frontal, temporal, and parietal regions using voxel-based morphometry, a technique used to assess brain volume. Reductions in the amount of tissue loss in these regions were observed as a function of fitness. Given that the brain structures most affected by aging also demonstrated the greatest fitness-related sparing, these initial findings provide a biological basis for fitness-related benefits to brain health during aging.

In a second study, Colcombe and colleagues (2006) examined the effects of aerobic fitness training on brain structure using a randomized controlled design with 59 sedentary healthy adults aged 60-79. The treatment group received a 6-month aerobic exercise (i.e., walking) intervention, while the control group received a stretching and toning intervention that did not include aerobic exercise. Results indicated that gray and white matter brain volume increased for those who received the aerobic fitness training intervention. No such results were observed for those assigned to the stretching and toning group. Specifically, those assigned to the aerobic training intervention demonstrated increased gray matter in the frontal lobes, including the dorsal anterior cingulate cortex, the supplementary motor area, the middle frontal gyrus, the dorsolateral region of the right inferior frontal gyrus, and the left superior temporal lobe. White matter volume changes also were evidenced following the aerobic fitness intervention, with increases in white matter tracts being observed within the anterior third of the corpus callosum. These brain regions are important for cognition, as they have been implicated in the cognitive control of attention and memory processes. These findings suggest that aerobic training not only spares age-related loss of brain structures but also may in fact enhance the structural health of specific brain regions.

In addition to the structural changes noted above, research has investigated the relationship between aerobic fitness and changes in brain function. That is, aerobic fitness training has also been observed to induce changes in patterns of functional activation. Functional MRI (fMRI) measures, which make it possible to image activity in the brain while an individual is performing a cognitive task, have revealed that aerobic training induces changes in patterns of functional activation. This approach involves inferring changes in neuronal activity from alteration in blood flow or metabolic activity in the brain. In a seminal paper, Colcombe and colleagues (2004) examined the relationship of aerobic fitness to brain function and cognition across two studies with older adults. In the first study, 41 older adult participants (mean age ~66) were divided into higher- and lower-fit groups based on their performance on a maximal exercise test. In the second study, 29 participants (aged 58-77) were recruited and randomly assigned to either a fitness training (i.e., walking) or control (i.e., stretching and toning) intervention. In both studies, participants were given a task requiring variable amounts of attention and inhibition. Results indicated that fitness (study 1) and fitness training (study 2) were related to greater activation in the middle frontal gyrus and superior parietal cortex; these regions of the brain are involved in attentional control and inhibitory functioning, processes entailed in the regulation of attention and action. These changes in neural activation were related to significant improvements in performance on the cognitive control task of attention and inhibition.

Taken together, the findings across studies suggest that an increase in aerobic fitness, derived from physical activity, is related to improvements in the integrity of brain structure and function and may underlie improvements in cognition across tasks requiring cognitive control. Although developmental differences exist, the general paradigm of this research can be applied to early stages of the life span, and some early attempts to do so have been made, as described below. Given the focus of this chapter on childhood cognition, it should be noted that this section has provided only a brief and arguably narrow look at the research on physical activity and cognitive aging. Considerable work has detailed the relationship of physical activity to other aspects of adult cognition using behavioral and neuroimaging tools (e.g., Boecker, 2011 ). The interested reader is referred to a number of review papers and meta-analyses describing the relationship of physical activity to various aspects of cognitive and brain health ( Etnier et al., 1997 ; Colcombe and Kramer, 2003 ; Tomporowski, 2003 ; Thomas et al., 2012 ).

Child Development, Brain Structure, and Function

Certain aspects of development have been linked with experience, indicating an intricate interplay between genetic programming and environmental influences. Gray matter, and the organization of synaptic connections in particular, appears to be at least partially dependent on experience (NRC/IOM, 2000; Taylor, 2006 ), with the brain exhibiting a remarkable ability to reorganize itself in response to input from sensory systems, other cortical systems, or insult ( Huttenlocher and Dabholkar, 1997 ). During typical development, experience shapes the pruning process through the strengthening of neural networks that support relevant thoughts and actions and the elimination of unnecessary or redundant connections. Accordingly, the brain responds to experience in an adaptive or “plastic” manner, resulting in the efficient and effective adoption of thoughts, skills, and actions relevant to one's interactions within one's environmental surroundings. Examples of neural plasticity in response to unique environmental interaction have been demonstrated in human neuroimaging studies of participation in music ( Elbert et al., 1995 ; Chan et al., 1998 ; Münte et al., 2001 ) and sports ( Hatfield and Hillman, 2001 ; Aglioti et al., 2008 ), thus supporting the educational practice of providing music education and opportunities for physical activity to children.

Effects of Regular Engagement in Physical Activity and Physical Fitness on Brain Structure

Recent advances in neuroimaging techniques have rapidly advanced understanding of the role physical activity and aerobic fitness may have in brain structure. In children a growing body of correlational research suggests differential brain structure related to aerobic fitness. Chaddock and colleagues (2010a , b ) showed a relationship among aerobic fitness, brain volume, and aspects of cognition and memory. Specifically, Chaddock and colleagues (2010a) assigned 9- to 10-year-old preadolescent children to lower- and higher-fitness groups as a function of their scores on a maximal oxygen uptake (VO 2 max) test, which is considered the gold-standard measure of aerobic fitness. They observed larger bilateral hippocampal volume in higher-fit children using MRI, as well as better performance on a task of relational memory. It is important to note that relational memory has been shown to be mediated by the hippocampus ( Cohen and Eichenbaum, 1993 ; Cohen et al., 1999 ). Further, no differences emerged for a task condition requiring item memory, which is supported by structures outside the hippocampus, suggesting selectivity among the aspects of memory that benefit from higher amounts of fitness. Lastly, hippocampal volume was positively related to performance on the relational memory task but not the item memory task, and bilateral hippocampal volume was observed to mediate the relationship between fitness and relational memory ( Chaddock et al., 2010a ). Such findings are consistent with behavioral measures of relational memory in children ( Chaddock et al., 2011 ) and neuroimaging findings in older adults ( Erickson et al., 2009 , 2011 ) and support the robust nonhuman animal literature demonstrating the effects of exercise on cell proliferation ( Van Praag et al., 1999 ) and survival ( Neeper et al., 1995 ) in the hippocampus.

In a second investigation ( Chaddock et al., 2010b ), higher- and lower-fit children (aged 9-10) underwent an MRI to determine whether structural differences might be found that relate to performance on a cognitive control task that taps attention and inhibition. The authors observed differential findings in the basal ganglia, a subcortical structure involved in the interplay of cognition and willed action. Specifically, higher-fit children exhibited greater volume in the dorsal striatum (i.e., caudate nucleus, putamen, globus pallidus) relative to lower-fit children, while no differences were observed in the ventral striatum. Such findings are not surprising given the role of the dorsal striatum in cognitive control and response resolution ( Casey et al., 2008 ; Aron et al., 2009 ), as well as the growing body of research in children and adults indicating that higher levels of fitness are associated with better control of attention, memory, and cognition ( Colcombe and Kramer, 2003 ; Hillman et al., 2008 ; Chang and Etnier, 2009 ). Chaddock and colleagues (2010b) further observed that higher-fit children exhibited increased inhibitory control and response resolution and that higher basal ganglia volume was related to better task performance. These findings indicate that the dorsal striatum is involved in these aspects of higher-order cognition and that fitness may influence cognitive control during preadolescent development. It should be noted that both studies described above were correlational in nature, leaving open the possibility that other factors related to fitness and/or the maturation of subcortical structures may account for the observed group differences.

Effects of Regular Engagement in Physical Activity and Physical Fitness on Brain Function

Other research has attempted to characterize fitness-related differences in brain function using fMRI and event-related brain potentials (ERPs), which are neuroelectric indices of functional brain activation in the electro-encephalographic time series. To date, few randomized controlled interventions have been conducted. Notably, Davis and colleagues (2011) conducted one such intervention lasting approximately 14 weeks that randomized 20 sedentary overweight preadolescent children into an after-school physical activity intervention or a nonactivity control group. The fMRI data collected during an antisaccade task, which requires inhibitory control, indicated increased bilateral activation of the prefrontal cortex and decreased bilateral activation of the posterior parietal cortex following the physical activity intervention relative to the control group. Such findings illustrate some of the neural substrates influenced by participation in physical activity. Two additional correlational studies ( Voss et al., 2011 ; Chaddock et al., 2012 ) compared higher- and lower-fit preadolescent children and found differential brain activation and superior task performance as a function of fitness. That is, Chaddock and colleagues (2012) observed increased activation in prefrontal and parietal brain regions during early task blocks and decreased activation during later task blocks in higher-fit relative to lower-fit children. Given that higher-fit children outperformed lower-fit children on the aspects of the task requiring the greatest amount of cognitive control, the authors reason that the higher-fit children were more capable of adapting neural activity to meet the demands imposed by tasks that tapped higher-order cognitive processes such as inhibition and goal maintenance. Voss and colleagues (2011) used a similar task to vary cognitive control requirements and found that higher-fit children outperformed their lower-fit counterparts and that such differences became more pronounced during task conditions requiring the upregulation of control. Further, several differences emerged across various brain regions that together make up the network associated with cognitive control. Collectively, these differences suggest that higher-fit children are more efficient in the allocation of resources in support of cognitive control operations.

Other imaging research has examined the neuroelectric system (i.e., ERPs) to investigate which cognitive processes occurring between stimulus engagement and response execution are influenced by fitness. Several studies ( Hillman et al., 2005 , 2009 ; Pontifex et al., 2011 ) have examined the P3 component of the stimulus-locked ERP and demonstrated that higher-fit children have larger-amplitude and shorter-latency ERPs relative to their lower-fit peers. Classical theory suggests that P3 relates to neuronal activity associated with revision of the mental representation of the previous event within the stimulus environment ( Donchin, 1981 ). P3 amplitude reflects the allocation of attentional resources when working memory is updated ( Donchin and Coles, 1988 ) such that P3 is sensitive to the amount of attentional resources allocated to a stimulus ( Polich, 1997 ; Polich and Heine, 2007 ). P3 latency generally is considered to represent stimulus evaluation and classification speed ( Kutas et al., 1977 ; Duncan-Johnson, 1981 ) and thus may be considered a measure of stimulus detection and evaluation time ( Magliero et al., 1984 ; Ila and Polich, 1999 ). Therefore the above findings suggest that higher-fit children allocate greater attentional resources and have faster cognitive processing speed relative to lower-fit children ( Hillman et al., 2005 , 2009 ), with additional research suggesting that higher-fit children also exhibit greater flexibility in the allocation of attentional resources, as indexed by greater modulation of P3 amplitude across tasks that vary in the amount of cognitive control required ( Pontifex et al., 2011 ). Given that higher-fit children also demonstrate better performance on cognitive control tasks, the P3 component appears to reflect the effectiveness of a subset of cognitive systems that support willed action ( Hillman et al., 2009 ; Pontifex et al., 2011 ).

Two ERP studies ( Hillman et al., 2009 ; Pontifex et al., 2011 ) have focused on aspects of cognition involved in action monitoring. That is, the error-related negativity (ERN) component was investigated in higher- and lower-fit children to determine whether differences in evaluation and regulation of cognitive control operations were influenced by fitness level. The ERN component is observed in response-locked ERP averages. It is often elicited by errors of commission during task performance and is believed to represent either the detection of errors during task performance ( Gehring et al., 1993 ; Holroyd and Coles, 2002 ) or more generally the detection of response conflict ( Botvinick et al., 2001 ; Yeung et al., 2004 ), which may be engendered by errors in response production. Several studies have reported that higher-fit children exhibit smaller ERN amplitude during rapid-response tasks (i.e., instructions emphasizing speed of responding; Hillman et al., 2009 ) and more flexibility in the allocation of these resources during tasks entailing variable cognitive control demands, as evidenced by changes in ERN amplitude for higher-fit children and no modulation of ERN in lower-fit children ( Pontifex et al., 2011 ). Collectively, this pattern of results suggests that children with lower levels of fitness allocate fewer attentional resources during stimulus engagement (P3 amplitude) and exhibit slower cognitive processing speed (P3 latency) but increased activation of neural resources involved in the monitoring of their actions (ERN amplitude). Alternatively, higher-fit children allocate greater resources to environmental stimuli and demonstrate less reliance on action monitoring (increasing resource allocation only to meet the demands of the task). Under more demanding task conditions, the strategy of lower-fit children appears to fail since they perform more poorly under conditions requiring the upregulation of cognitive control.

Finally, only one randomized controlled trial published to date has used ERPs to assess neurocognitive function in children. Kamijo and colleagues (2011) studied performance on a working memory task before and after a 9-month physical activity intervention compared with a wait-list control group. They observed better performance following the physical activity intervention during task conditions that required the upregulation of working memory relative to the task condition requiring lesser amounts of working memory. Further, increased activation of the contingent negative variation (CNV), an ERP component reflecting cognitive and motor preparation, was observed at posttest over frontal scalp sites in the physical activity intervention group. No differences in performance or brain activation were noted for the wait-list control group. These findings suggest an increase in cognitive preparation processes in support of a more effective working memory network resulting from prolonged participation in physical activity. For children in a school setting, regular participation in physical activity as part of an after-school program is particularly beneficial for tasks that require the use of working memory.

Adiposity and Risk for Metabolic Syndrome as It Relates to Cognitive Health

A related and emerging literature that has recently been popularized investigates the relationship of adiposity to cognitive and brain health and academic performance. Several reports ( Datar et al., 2004 ; Datar and Sturm, 2006 ; Judge and Jahns, 2007 ; Gable et al., 2012 ) on this relationship are based on large-scale datasets derived from the Early Child Longitudinal Study. Further, nonhuman animal research has been used to elucidate the relationships between health indices and cognitive and brain health (see Figure 4-4 for an overview of these relationships). Collectively, these studies observed poorer future academic performance among children who entered school overweight or moved from a healthy weight to overweight during the course of development. Corroborating evidence for a negative relationship between adiposity and academic performance may be found in smaller but more tightly controlled studies. As noted above, Castelli and colleagues (2007) observed poorer performance on the mathematics and reading portions of the Illinois Standardized Achievement Test in 3rd- and 5th-grade students as a function of higher BMI, and Donnelly and colleagues (2009) used a cluster randomized trial to demonstrate that physical activity in the classroom decreased BMI and improved academic achievement among pre-adolescent children.

Relationships between health indices and cognitive and brain health. NOTE: AD = Alzheimer's disease; PD = Parkinson's disease. SOURCE: Cotman et al., 2007. Reprinted with permission.

Recently published reports describe the relationship between adiposity and cognitive and brain health to advance understanding of the basic cognitive processes and neural substrates that may underlie the adiposity-achievement relationship. Bolstered by findings in adult populations (e.g., Debette et al., 2010 ; Raji et al., 2010 ; Carnell et al., 2011 ), researchers have begun to publish data on preadolescent populations indicating differences in brain function and cognitive performance related to adiposity (however, see Gunstad et al., 2008 , for an instance in which adiposity was unrelated to cognitive outcomes). Specifically, Kamijo and colleagues (2012a) examined the relationship of weight status to cognitive control and academic achievement in 126 children aged 7-9. The children completed a battery of cognitive control tasks, and their body composition was assessed using dual X-ray absorptiometry (DXA). The authors found that higher BMI and greater amounts of fat mass (particularly in the midsection) were related to poorer performance on cognitive control tasks involving inhibition, as well as lower academic achievement. In follow-up studies, Kamijo and colleagues (2012b) investigated whether neural markers of the relationship between adiposity and cognition may be found through examination of ERP data. These studies compared healthy-weight and obese children and found a differential distribution of the P3 potential (i.e., less frontally distributed) and larger N2 amplitude, as well as smaller ERN magnitude, in obese children during task conditions that required greater amounts of inhibitory control ( Kamijo et al., 2012c ). Taken together, the above results suggest that obesity is associated with less effective neural processes during stimulus capture and response execution. As a result, obese children perform tasks more slowly ( Kamijo et al., 2012a ) and are less accurate ( Kamijo et al., 2012b , c ) in response to tasks requiring variable amounts of cognitive control. Although these data are correlational, they provide a basis for further study using other neuroimaging tools (e.g., MRI, fMRI), as well as a rationale for the design and implementation of randomized controlled studies that would allow for causal interpretation of the relationship of adiposity to cognitive and brain health. The next decade should provide a great deal of information on this relationship.

  • LIMITATIONS

Despite the promising findings described in this chapter, it should be noted that the study of the relationship of childhood physical activity, aerobic fitness, and adiposity to cognitive and brain health and academic performance is in its early stages. Accordingly, most studies have used designs that afford correlation rather than causation. To date, in fact, only two randomized controlled trials ( Davis et al., 2011 ; Kamijo et al., 2011 ) on this relationship have been published. However, several others are currently ongoing, and it was necessary to provide evidence through correlational studies before investing the effort, time, and funding required for more demanding causal studies. Given that the evidence base in this area has grown exponentially in the past 10 years through correlational studies and that causal evidence has accumulated through adult and nonhuman animal studies, the next step will be to increase the amount of causal evidence available on school-age children.

Accomplishing this will require further consideration of demographic factors that may moderate the physical activity–cognition relationship. For instance, socioeconomic status has a unique relationship with physical activity ( Estabrooks et al., 2003 ) and cognitive control ( Mezzacappa, 2004 ). Although many studies have attempted to control for socioeconomic status (see Hillman et al., 2009 ; Kamijo et al., 2011 , 2012a , b , c ; Pontifex et al., 2011 ), further inquiry into its relationship with physical activity, adiposity, and cognition is warranted to determine whether it may serve as a potential mediator or moderator for the observed relationships. A second demographic factor that warrants further consideration is gender. Most authors have failed to describe gender differences when reporting on the physical activity–cognition literature. However, studies of adiposity and cognition have suggested that such a relationship may exist (see Datar and Sturm, 2006 ). Additionally, further consideration of age is warranted. Most studies have examined a relatively narrow age range, consisting of a few years. Such an approach often is necessary because of maturation and the need to develop comprehensive assessment tools that suit the various stages of development. However, this approach has yielded little understanding of how the physical activity–cognition relationship may change throughout the course of maturation.

Finally, although a number of studies have described the relationship of physical activity, fitness, and adiposity to standardized measures of academic performance, few attempts have been made to observe the relationship within the context of the educational environment. Standardized tests, although necessary to gauge knowledge, may not be the most sensitive measures for (the process of) learning. Future research will need to do a better job of translating promising laboratory findings to the real world to determine the value of this relationship in ecologically valid settings.

From an authentic and practical to a mechanistic perspective, physically active and aerobically fit children consistently outperform their inactive and unfit peers academically on both a short- and a long-term basis. Time spent engaged in physical activity is related not only to a healthier body but also to enriched cognitive development and lifelong brain health. Collectively, the findings across the body of literature in this area suggest that increases in aerobic fitness, derived from physical activity, are related to improvements in the integrity of brain structure and function that underlie academic performance. The strongest relationships have been found between aerobic fitness and performance in mathematics, reading, and English. For children in a school setting, regular participation in physical activity is particularly beneficial with respect to tasks that require working memory and problem solving. These findings are corroborated by the results of both authentic correlational studies and experimental randomized controlled trials. Overall, the benefits of additional time dedicated to physical education and other physical activity opportunities before, during, and after school outweigh the benefits of exclusive utilization of school time for academic learning, as physical activity opportunities offered across the curriculum do not inhibit academic performance.

Both habitual and single bouts of physical activity contribute to enhanced academic performance. Findings indicate a robust relationship of acute exercise to increased attention, with evidence emerging for a relationship between participation in physical activity and disciplinary behaviors, time on task, and academic performance. Specifically, higher-fit children allocate greater resources to a given task and demonstrate less reliance on environmental cues or teacher prompting.

  • Åberg MA, Pedersen NL, Torén K, Svartengren M, Bäckstrand B, Johnsson T, Cooper-Kuhn CM, Åberg ND, Nilsson M, Kuhn HG. Cardiovascular fitness is associated with cognition in young adulthood. Proceedings of the National Academy of Sciences of the United States of America. 2009; 106 (49):20906–20911. [ PMC free article : PMC2785721 ] [ PubMed : 19948959 ]
  • Aglioti SM, Cesari P, Romani M, Urgesi C. Action anticipation and motor resonance in elite basketball players. Nature Neuroscience. 2008; 11 (9):1109–1116. [ PubMed : 19160510 ]
  • Ahamed Y, Macdonald H, Reed K, Naylor PJ, Liu-Ambrose T, McKay H. School-based physical activity does not compromise children's academic performance. Medicine and Science in Sports and Exercise. 2007; 39 (2):371–376. [ PubMed : 17277603 ]
  • Aron A, Poldrack R, Wise S. Cognition: Basal ganglia role. Encyclopedia of Neuroscience. 2009; 2 :1069–1077.
  • Barros RM, Silver EJ, Stein REK. School recess and group classroom behavior. Pediatrics. 2009; 123 (2):431–436. [ PubMed : 19171606 ]
  • Bartholomew JB, Jowers EM. Physically active academic lessons in elementary children. Preventive Medicine. 2011; 52 (Suppl 1):S51–S54. [ PMC free article : PMC3116963 ] [ PubMed : 21281672 ]
  • Basch C. Healthier children are better learners: A missing link in school reforms to close the achievement gap. 2010. [October 11, 2011]. http://www ​.equitycampaign ​.org/i/a/document ​/12557_EquityMattersVol6_Web03082010 ​.pdf . [ PubMed : 21923870 ]
  • Baxter SD, Royer JA, Hardin JW, Guinn CH, Devlin CM. The relationship of school absenteeism with body mass index, academic achievement, and socioeconomic status among fourth grade children. Journal of School Health. 2011; 81 (7):417–423. [ PMC free article : PMC3972016 ] [ PubMed : 21668882 ]
  • Benden ME, Blake JJ, Wendel ML, Huber JC Jr. The impact of stand-biased desks in classrooms on calorie expenditure in children. American Journal of Public Health. 2011; 101 (8):1433–1436. [ PMC free article : PMC3134494 ] [ PubMed : 21421945 ]
  • Biddle SJ, Asare M. Physical activity and mental health in children and adolescents: A review of reviews. British Journal of Sports Medicine. 2011; 45 (11):886–895. [ PubMed : 21807669 ]
  • Blair C, Zelazo PD, Greenberg MT. The measurement of executive function in early childhood. Developmental Neuropsychology. 2005; 28 (2):561–571. [ PubMed : 16144427 ]
  • Boecker H. On the emerging role of neuroimaging in determining functional and structural brain integrity induced by physical exercise: Impact for predictive, preventive, and personalized medicine. EPMA Journal. 2011; 2 (3):277–285. [ PMC free article : PMC3405390 ] [ PubMed : 23199163 ]
  • Botvinick MM, Braver TS, Barch DM, Carter CS, Cohen JD. Conflict monitoring and cognitive control. Psychological Review. 2001; 108 (3):624. [ PubMed : 11488380 ]
  • Budde H, Voelcker-Rehage C, S-Pietrabyk Kendziorra, Ribeiro P, Tidow G. Acute coordinative exercise improves attentional performance in adolescents. Neuroscience Letters. 2008; 441 (2):219–223. [ PubMed : 18602754 ]
  • Burkhalter TM, Hillman CH. A narrative review of physical activity, nutrition, and obesity to cognition and scholastic performance across the human lifespan. Advances in Nutrition. 2011; 2 (2):201S–206S. [ PMC free article : PMC3065760 ] [ PubMed : 22332052 ]
  • Carlson SA, Fulton JE, Lee SM, Maynard LM, Brown DR, Kohl HW III, Dietz WH. Physical education and academic achievement in elementary school: Data from the Early Childhood Longitudinal Study. American Journal of Public Health. 2008; 98 (4):721–727. [ PMC free article : PMC2377002 ] [ PubMed : 18309127 ]
  • Carnell S, Gibson C, Benson L, Ochner C, Geliebter A. Neuroimaging and obesity: Current knowledge and future directions. Obesity Reviews. 2011; 13 (1):43–56. [ PMC free article : PMC3241905 ] [ PubMed : 21902800 ]
  • Casey B, Jones RM, Hare TA. The adolescent brain. Annals of the New York Academy of Sciences. 2008; 1124 (1):111–126. [ PMC free article : PMC2475802 ] [ PubMed : 18400927 ]
  • Castelli DM, Hillman CH, Buck SM, Erwin HE. Physical fitness and academic achievement in third- and fifth-grade students. Journal of Sport and Exercise Psychology. 2007; 29 (2):239–252. [ PubMed : 17568069 ]
  • Chaddock L, Erickson KI, Prakash RS, Kim JS, Voss MW, VanPatter M, Pontifex MB, Raine LB, Konkel A, Hillman CH. A neuroimaging investigation of the association between aerobic fitness, hippocampal volume, and memory performance in preadolescent children. Brain Research. 2010a; 1358 :172–183. [ PMC free article : PMC3953557 ] [ PubMed : 20735996 ]
  • Chaddock L, Erickson KI, Prakash RS, VanPatter M, Voss MW, Pontifex MB, Raine LB, Hillman CH, Kramer AF. Basal ganglia volume is associated with aerobic fitness in preadolescent children. Developmental Neuroscience. 2010b; 32 (3):249–256. [ PMC free article : PMC3696376 ] [ PubMed : 20693803 ]
  • Chaddock L, Hillman CH, Buck SM, Cohen NJ. Aerobic fitness and executive control of relational memory in preadolescent children. Medicine and Science in Sports and Exercise. 2011; 43 (2):344. [ PubMed : 20508533 ]
  • Chaddock L, Erickson KI, Prakash RS, Voss MW, VanPatter M, Pontifex MB, Hillman CH, Kramer AF. A functional MRI investigation of the association between childhood aerobic fitness and neurocognitive control. Biological Psychology. 2012; 89 (1):260–268. [ PubMed : 22061423 ]
  • Chan AS, Ho YC, Cheung MC. Music training improves verbal memory. Nature. 1998; 396 (6707):128. [ PubMed : 9823892 ]
  • Chang YK, Etnier JL. Effects of an acute bout of localized resistance exercise on cognitive performance in middle-aged adults: A randomized controlled trial study. Psychology of Sport and Exercise. 2009; 10 (1):19–24.
  • Chih CH, Chen JF. The relationship between physical education performance, fitness tests, and academic achievement in elementary school. International Journal of Sport and Society. 2011; 2 (1):65–73.
  • Chomitz VR, Slining MM, McGowan RJ, Mitchell SE, Dawson GF, Hacker KA. Is there a relationship between physical fitness and academic achievement? Positive results from public school children in the northeastern United States. Journal of School Health. 2008; 79 (1):30–37. [ PubMed : 19149783 ]
  • Coe DP, Pivarnik JM, Womack CJ, Reeves MJ, Malina RM. Effect of physical education and activity levels on academic achievement in children. Medicine and Science in Sports and Exercise. 2006; 38 (8):1515–1519. [ PubMed : 16888468 ]
  • Cohen NJ, Eichenbaum H. Memory, amnesia, and the hippocampal system. Cambridge, MA: MIT Press; 1993.
  • Cohen NJ, Ryan J, Hunt C, Romine L, Wszalek T, Nash C. Hippocampal system and declarative (relational) memory: Summarizing the data from functional neuroimaging studies. Hippocampus. 1999; 9 (1):83–98. [ PubMed : 10088903 ]
  • Colcombe SJ, Kramer AF. Fitness effects on the cognitive function of older adults a meta-analytic study. Psychological Science. 2003; 14 (2):125–130. [ PubMed : 12661673 ]
  • Colcombe SJ, Erickson KI, Raz N, Webb AG, Cohen NJ, McAuley E, Kramer AF. Aerobic fitness reduces brain tissue loss in aging humans. Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2003; 58 (2):M176–M180. [ PubMed : 12586857 ]
  • Colcombe SJ, Kramer AF, Erickson KI, Scalf P, McAuley E, Cohen NJ, Webb A, Jerome GJ, Marquez DX, Elavsky S. Cardiovascular fitness, cortical plasticity, and aging. Proceedings of the National Academy of Sciences of the United States of America. 2004; 101 (9):3316–3321. [ PMC free article : PMC373255 ] [ PubMed : 14978288 ]
  • Colcombe SJ, Erickson KI, Scalf PE, Kim JS, Prakash R, McAuley E, Elavsky S, Marquez DX, Hu L, Kramer AF. Aerobic exercise training increases brain volume in aging humans. Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2006; 61 (11):1166–1170. [ PubMed : 17167157 ]
  • Cooper K, Everett D, Kloster J, Meredith MD, Rathbone M, Read K. Preface: Texas statewide assessment of youth fitness. Research Quarterly for Exercise and Sport. 2010; 81 (3):ii. [ PubMed : 21049831 ]
  • Cotman CW, Berchtold NC, Christie LA. Exercise builds brain health: Key roles of growth factor cascades and inflammation. Trends in Neurosciences. 2007; 30 (9):464–472. [ PubMed : 17765329 ]
  • Cottrell LA, Northrup K, Wittberg R. The extended relationship between child cardiovascular risks and academic performance measures. Obesity (Silver Spring). 2007; 15 (12):3170–3177. [ PubMed : 18198328 ]
  • Crosnoe R. Academic and health-related trajectories in high school: The intersection of gender and athletics. Journal of Health and Social Behavior. 2002; 43 :317–335. [ PubMed : 12467256 ]
  • Daley AJ, Ryan J. Academic performance and participation in physical activity by secondary school adolescents. Perceptual and Motor Skills. 2000; 91 (2):531–534. [ PubMed : 11065314 ]
  • Datar A, Sturm R. Physical education in elementary school and body mass index: Evidence from the Early Childhood Longitudinal Study. Journal Information. 2004; 94 (9):1501–1509. [ PMC free article : PMC1448481 ] [ PubMed : 15333302 ]
  • Datar A, Sturm R. Childhood overweight and elementary school outcomes. International Journal of Obesity. 2006; 30 (9):1449–1460. [ PubMed : 16534518 ]
  • Datar A, Sturm R, Magnabosco JL. Childhood overweight and academic performance: National study of kindergartners and first-graders. Obesity Research. 2004; 12 (1):58–68. [ PubMed : 14742843 ]
  • Davidson MC, Amso D, Anderson LC, Diamond A. Development of cognitive control and executive functions from 4 to 13 years: Evidence from manipulations of memory, inhibition, and task switching. Neuropsychologia. 2006; 44 (11):2037. [ PMC free article : PMC1513793 ] [ PubMed : 16580701 ]
  • Davis CL, Tomporowski PD, McDowell JE, Austin BP, Miller PH, Yanasak NE, Allison JD, Naglieri JA. Exercise improves executive function and achievement and alters brain activation in overweight children: A randomized, controlled trial. Health Psychology. 2011; 30 (1):91–98. [ PMC free article : PMC3057917 ] [ PubMed : 21299297 ]
  • Dawson P, Guare R. Executive skills in children and adolescents: A practical guide to assessment and intervention. New York: Guilford Press; 2004. pp. 2–8.
  • Debette S, Beiser A, Hoffmann U, DeCarli C, O'Donnell CJ, Massaro JM, Au R, Himali JJ, Wolf PA, Fox CS, Seshadri S. Visceral fat is associated with lower brain volume in healthy middle-aged adults. Annals of Neurology. 2010; 68 :136–144. [ PMC free article : PMC2933649 ] [ PubMed : 20695006 ]
  • Dexter TT. Relationships between sport knowledge, sport performance and academic ability: Empirical evidence from GCSE physical education. Journal of Sports Sciences. 1999; 17 (4):283–295. [ PubMed : 10373038 ]
  • Diamond A. The early development of executive functions. In: Bialystok E, Craik FIM, editors. In Lifespan cognition: Mechanisms of change. New York: Oxford University Press; 2006. pp. 70–95.
  • Donchin E. Surprise! … surprise. Psychophysiology. 1981; 18 (5):493–513. [ PubMed : 7280146 ]
  • Donchin E, Coles MGH. Is the P300 component a manifestation of context updating. Behavioral and Brain Sciences. 1988; 11 (03):357–374.
  • Donnelly JE, Lambourne K. Classroom-based physical activity, cognition, and academic achievement. Preventive Medicine. 2011; 52 (Suppl 1):S36–S42. [ PubMed : 21281666 ]
  • Donnelly JE, Greene JL, Gibson CA, Smith BK, Washburn RA, Sullivan DK, DuBose K, Mayo MS, Schmelzle KH, Ryan JJ. Physical Activity Across the Curriculum (PAAC): A randomized controlled trial to promote physical activity and diminish overweight and obesity in elementary school children. Preventive Medicine. 2009; 49 (4):336–341. [ PMC free article : PMC2766439 ] [ PubMed : 19665037 ]
  • Drollette ES, Shishido T, Pontifex MB, Hillman CH. Maintenance of cognitive control during and after walking in preadolescent children. Medicine and Science in Sports and Exercise. 2012; 44 (10):2017–2024. [ PubMed : 22525770 ]
  • Duncan SC, Duncan TE, Strycker LA, Chaumeton NR. A cohort-sequential latent growth model of physical activity from ages 12 to 17 years. Annals of Behavioral Medicine. 2007; 33 (1):80–89. [ PMC free article : PMC2729662 ] [ PubMed : 17291173 ]
  • Duncan-Johnson CC. P3 latency: A new metric of information processing. Psychophysiology. 1981; 18 :207–215. [ PubMed : 7291436 ]
  • Dwyer T, Coonan W, Worsley A, Leitch D. An assessment of the effects of two physical activity programmes on coronary heart disease risk factors in primary school children. Community Health Studies. 1979; 3 (3):196–202.
  • Dwyer T, Coonan WE, Leitch DR, Hetzel BS, Baghurst R. An investigation of the effects of daily physical activity on the health of primary school students in south Australia. International Journal of Epidemiology. 1983; 12 (3):308–313. [ PubMed : 6629620 ]
  • Edwards JU, Mauch L, Winkleman MR. Relationship of nutrition and physical activity behaviors and fitness measures to academic performance for sixth graders in a Midwest city school district. Journal of School Health. 2011; 81 :65–73. [ PubMed : 21223273 ]
  • Efrat M. The relationship between low-income and minority children's physical activity and academic-related outcomes: A review of the literature. Health Education and Behavior. 2011; 38 (5):441–451. [ PubMed : 21285376 ]
  • Eitle TM. Do gender and race matter? Explaining the relationship between sports participation and achievement. Sociological Spectrum. 2005; 25 (2):177–195.
  • Eitle TM, Eitle DJ. Sociology of Education. 2002. Race, cultural capital, and the educational effects of participation in sports; pp. 123–146.
  • Elbert T, Pantev C, Wienbruch C, Rockstroh B, Taub E. Increased cortical representation of the fingers of the left hand in string players. Science. 1995; 270 (5234):305–307. [ PubMed : 7569982 ]
  • Elder C, Leaver-Dunn D, Wang MQ, Nagy S, Green L. Organized group activity as a protective factor against adolescent substance use. American Journal of Health Behavior. 2000; 24 (2):108–113.
  • Ellemberg D, St-Louis-Deschênes M. The effect of acute physical exercise on cognitive function during development. Psychology of Sport and Exercise. 2010; 11 (2):122–126.
  • Erickson KI, Prakash RS, Voss MW, Chaddock L, Hu L, Morris KS, White SM, Wójcicki TR, McAuley E, Kramer AF. Aerobic fitness is associated with hippocampal volume in elderly humans. Hippocampus. 2009; 19 (10):1030–1039. [ PMC free article : PMC3072565 ] [ PubMed : 19123237 ]
  • Erickson KI, Voss MW, Prakash RS, Basak C, Szabo A, Chaddock L, Kim JS, Heo S, Alves H, White SM. Exercise training increases size of hippocampus and improves memory. Proceedings of the National Academy of Sciences of the United States of America. 2011; 108 (7):3017–3022. [ PMC free article : PMC3041121 ] [ PubMed : 21282661 ]
  • Ericsson KA, Charness N. Expert performance: Its structure and acquisition. American Psychologist. 1994; 49 (8):725.
  • Estabrooks AP, Lee RE, Gyurcsik NC. Resources for physical activity participation: Does availability and accessibility differ by neighborhood socioeconomic status. Annals of Behavioral Medicine. 2003; 25 (2):100–104. [ PubMed : 12704011 ]
  • Etnier JL, Salazar W, Landers DM, Petruzzello SJ, Han M, Nowell P. The influence of physical fitness and exercise upon cognitive functioning: A meta-analysis. Journal of Sport and Exercise Psychology. 1997; 19 (3):249–277.
  • Etnier JL, Nowell PM, Landers DM, Sibley BA. A meta-regression to examine the relationship between aerobic fitness and cognitive performance. Brain Research Reviews. 2006; 52 (1):119–130. [ PubMed : 16490256 ]
  • Eveland-Sayers BM, Farley RS, Fuller DK, Morgan DW, Caputo JL. Physical fitness and academic achievement in elementary school children. Journal of Physical Activity and Health. 2009; 6 (1):99. [ PubMed : 19211963 ]
  • Fan X, Chen M. Parental involvement and students' academic achievement: A meta-analysis. Educational Psychology Review. 2001; 13 (1):1–22.
  • Fedewa AL, Ahn S. The effects of physical activity and physical fitness on children's achievement and cognitive outcomes: A meta-analysis. Research Quarterly for Exercise and Sport. 2011; 82 (3):521–535. [ PubMed : 21957711 ]
  • Fisher M, Juszczak L, Friedman SB. Sports participation in an urban high school: Academic and psychologic correlates. Journal of Adolescent Health. 1996; 18 (5):329–334. [ PubMed : 9156545 ]
  • Fox CK, Barr-Anderson D, D-Neumark Sztainer, Wall M. Physical activity and sports team participation: Associations with academic outcomes in middle school and high school students. Journal of School Health. 2010; 80 (1):31–37. [ PubMed : 20051088 ]
  • Fredericks CR, Kokot SJ, Krog S. Using a developmental movement programme to enhance academic skills in grade 1 learners. South African Journal for Research in Sport, Physical Education and Recreation. 2006; 28 (1):29–42.
  • Gabbard C, Barton J. Effects of physical activity on mathematical computation among young children. Journal of Psychology. 1979; 103 :287–288.
  • Gable S, Krull JL, Chang Y. Boys' and girls' weight status and math performance from kindergarten entry through fifth grade: A mediated analysis. Child Development. 2012; 83 (5):1822–1839. [ PubMed : 22694240 ]
  • Gehring WJ, Goss B, Coles MG, Meyer DE, Donchin E. A neural system for error detection and compensation. Psychological Science. 1993; 4 (6):385–390.
  • Getlinger MJ, Laughlin V, Bell E, Akre C, Arjmandi BH. Food waste is reduced when elementary-school children have recess before lunch. Journal of the American Dietetic Association. 1996; 96 (9):906. [ PubMed : 8784336 ]
  • Glenmark B. Skeletal muscle fiber types, physical performance, physical activity and attitude to physical activity in women and men: A follow-up from age 16-27. Acta Physiologica Scandinavica Supplementum. 1994; 623 :1–47. [ PubMed : 7942046 ]
  • Grieco LA, Jowers EM, Bartholomew JB. Physically active academic lessons and time on task: The moderating effect of body mass index. Medicine and Science in Sports and Exercise. 2009; 41 (10):1921–1926. [ PubMed : 19727020 ]
  • Grissom JB. Physical fitness and academic achievement. Journal of Exercise Physiology Online. 2005; 8 (1):11–25.
  • Gunstad J, Spitznagel MB, Paul RH, Cohen RA, Kohn M, Luyster FS, Clark R, Williams LM, Gordon E. Body mass index and neuropsychological function in healthy children and adolescents. Appetite. 2008; 5 (2):246–51. [ PubMed : 17761359 ]
  • Hanson SL, Kraus RS. Women, sports, and science: Do female athletes have an advantage. Sociology of Education. 1998; 71 :93–110.
  • Hatfield BD, Hillman CH. The psychophysiology of sport: A mechanistic understanding of the psychology of superior performance. In: Singer RN, Hausenblas HA, Janelle C, editors. In The handbook of research on sport psychology. 2nd. New York: John Wiley; 2001. pp. 362–386.
  • Hillman CH, Snook EM, Jerome GJ. Acute cardiovascular exercise and executive control function. International Journal of Psychophysiology. 2003; 48 (3):307–314. [ PubMed : 12798990 ]
  • Hillman CH, Castelli DM, Buck SM. Aerobic fitness and neurocognitive function in healthy preadolescent children. Medicine and Science in Sports and Exercise. 2005; 37 (11):1967. [ PubMed : 16286868 ]
  • Hillman CH, Motl RW, Pontifex MB, Posthuma D, Stubbe JH, Boomsma DI, De Geus EJC. Physical activity and cognitive function in a cross-section of younger and older community-dwelling individuals. Health Psychology. 2006; 25 (6):678. [ PubMed : 17100496 ]
  • Hillman CH, Erickson KI, Kramer AF. Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience. 2008; 9 (1):58–65. [ PubMed : 18094706 ]
  • Hillman CH, Pontifex MB, Raine LB, Castelli DM, Hall EE, Kramer AF. The effect of acute treadmill walking on cognitive control and academic achievement in preadolescent children. Neuroscience. 2009; 159 (3):1044. [ PMC free article : PMC2667807 ] [ PubMed : 19356688 ]
  • Holroyd CB, Coles MG. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review. 2002; 109 (4):679. [ PubMed : 12374324 ]
  • Huttenlocher PR, Dabholkar AS. Regional differences in synaptogenesis in human cerebral cortex. Journal of Comparative Neurology. 1997; 387 (2):167–178. [ PubMed : 9336221 ]
  • Ila AB, Polich J. P300 and response time from a manual Stroop task. Clinical Neurophysiology. 1999; 110 (2):367–373. [ PubMed : 10210626 ]
  • Jarrett OS, Maxwell DM, Dickerson C, Hoge P, Davies G, Yetley A. Impact of recess on classroom behavior: Group effects and individual differences. Journal of Educational Research. 1998; 92 (2):121–126.
  • Jones JG, Hardy L. Stress and cognitive functioning in sport. Journal of Sports Sciences. 1989; 7 (1):41–63. [ PubMed : 2659817 ]
  • Judge S, Jahns L. Association of overweight with academic performance and social and behavioral problems: An update from the Early Childhood Longitudinal Study. Journal of School Health. 2007; 77 :672–678. [ PubMed : 18076412 ]
  • Kamijo K, Pontifex MB, O'Leary KC, Scudder MR, Wu CT, Castelli DM, Hillman CH. The effects of an afterschool physical activity program on working memory in preadolescent children. Developmental Science. 2011; 14 (5):1046–1058. [ PMC free article : PMC3177170 ] [ PubMed : 21884320 ]
  • Kamijo K, Khan NA, Pontifex MB, Scudder MR, Drollette ES, Raine LB, Evans EM, Castelli DM, Hillman CH. The relation of adiposity to cognitive control and scholastic achievement in preadolescent children. Obesity. 2012a; 20 (12):2406–2411. [ PMC free article : PMC3414677 ] [ PubMed : 22546743 ]
  • Kamijo K, Pontifex MB, Khan NA, Raine LB, Scudder MR, Drollette ES, Evans EM, Castelli DM, Hillman CH. The association of childhood obesity to neuroelectric indices of inhibition. Psychophysiology. 2012b; 49 (10):1361–1371. [ PubMed : 22913478 ]
  • Kamijo K, Pontifex MB, Khan NA, Raine LB, Scudder MR, Drollette ES, Evans EM, Castelli DM, Hillman CH. Cerebral Cortex. 2012c. [October 4, 2013]. The negative association of childhood obesity to the cognitive control of action monitoring. Epub ahead of print, November 11. cercor ​.oxfordjournals ​.org/content/early/2012/11/09/cercor ​.bhs349.long . [ PMC free article : PMC3920765 ] [ PubMed : 23146965 ]
  • Kibbe DL, Hackett J, Hurley M, McFarland A, Schubert KG, Schultz A, Harris S. Ten years of TAKE 10! ® : Integrating physical activity with academic concepts in elementary school classrooms. Preventive Medicine. 2011; 52 (Suppl):S43–S50. [ PubMed : 21281670 ]
  • Kramer AF, Erickson KI. Capitalizing on cortical plasticity: Influence of physical activity on cognition and brain function. Trends in Cognitive Sciences. 2007; 11 (8):342–348. [ PubMed : 17629545 ]
  • Kramer AF, Hahn S, Cohen NJ, Banich MT, McAuley E, Harrison CR, Chason J, Vakil E, Bardell L, Boileau RA. Ageing, fitness and neurocognitive function. Nature. 1999; 400 (6743):418–419. [ PubMed : 10440369 ]
  • Kutas M, McCarthy G, Donchin E. Augmenting mental chronometry: The P300 as a measure of stimulus evaluation time. Science. 1977; 197 (4305):792–795. [ PubMed : 887923 ]
  • London RA, Castrechini S. A longitudinal examination of the link between youth physical fitness and academic achievement. Journal of School Health. 2011; 81 (7):400–408. [ PubMed : 21668880 ]
  • MacDonald AW, Cohen JD, Stenger VA, Carter CS. Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science. 2000; 288 (5472):1835–1838. [ PubMed : 10846167 ]
  • Magliero A, Bashore TR, Coles MG, Donchin E. On the dependence of P300 latency on stimulus evaluation processes. Psychophysiology. 1984; 21 (2):171–186. [ PubMed : 6728983 ]
  • Mahar MT, Murphy SK, Rowe DA, Golden J, Shields AT, Raedeke TD. Effects of a classroom-based program on physical activity and on-task behavior. Medicine and Science in Sports and Exercise. 2006; 38 (12):2086. [ PubMed : 17146314 ]
  • Mechanic D, Hansell S. Adolescent competence, psychological well-being, and self-assessed physical health. Journal of Health and Social Behavior. 1987; 28 (4):364–374. [ PubMed : 3429806 ]
  • Mezzacappa E. Alerting, orienting, and executive attention: Developmental properties and sociodemographic correlates in an epidemiological sample of young, urban children. Child Development. 2004; 75 (5):1373–1386. [ PubMed : 15369520 ]
  • Miller KE, Melnick MJ, Barnes GM, Farrell MP, Sabo D. Untangling the links among the athletic involvement, gender, race, and adolescent academic outcomes. Sociology of Sport. 2005; 22 (2):178–193. [ PMC free article : PMC1343519 ] [ PubMed : 16467902 ]
  • Monti JM, Hillman CH, Cohen NJ. Aerobic fitness enhances relational memory in preadolescent children: The FITKids randomized control trial. Hippocampus. 2012; 22 (9):1876–1882. [ PMC free article : PMC3404196 ] [ PubMed : 22522428 ]
  • Münte TF, Kohlmetz C, Nager W, Altenmüller E. Superior auditory spatial tuning in conductors. Nature. 2001; 409 (6820):580. [ PubMed : 11214309 ]
  • NASPE (National Association for Sport and Physical Education). Moving into the future: National Physical Education Content Standards. 2nd. Reston, VA: NASPE; 2004.
  • NASPE. Recess for elementary school students. 2006. [December 1, 2012]. http://www ​.aahperd.org ​/naspe/standards/upload ​/recess-for-elementary-school-students-2006.pdf .
  • Neeper SA, Gomez-Pinilla F, Choi J, Cotman C. Exercise and brain neuro-trophins. Nature. 1995; 373 (6510):109. [ PubMed : 7816089 ]
  • NRC (National Research Council)/IOM (Institute of Medicine). From neurons to neighborhoods: The science of early childhood development. Washington, DC: National Academy Press; 2000. [ PubMed : 25077268 ]
  • O'Leary KC, Pontifex MB, Scudder MR, Brown ML, Hillman CH. The effects of single bouts of aerobic exercise, exergaming, and videogame play on cognitive control. Clinical Neurophysiology. 2011; 122 (8):1518–1525. [ PubMed : 21353635 ]
  • Page RM, Hammermeister J, Scanlan A, Gilbert L. Is school sports participation a protective factor against adolescent health risk behaviors. Journal of Health Education. 1998; 29 (3):186–192.
  • Pellegrini AD, Bohn CM. The role of recess in children's cognitive performance and school adjustment. Educational Researcher. 2005; 34 (1):13–19.
  • Pellegrini AD, Huberty PD, Jones I. The effects of recess timing on children's playground and classroom behaviors. American Educational Research Journal. 1995; 32 (4):845–864.
  • Pesce C, Crova C, Cereatti L, Casella R, Bellucci M. Physical activity and mental performance in preadolescents: Effects of acute exercise on free-recall memory. Mental Health and Physical Activity. 2009; 2 (1):16–22.
  • Polich J. EEG and ERP assessment of normal aging. Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section. 1997; 104 (3):244–256. [ PubMed : 9186239 ]
  • Polich J, Heine MR. P300 topography and modality effects from a single-stimulus paradigm. Psychophysiology. 2007; 33 (6):747–752. [ PubMed : 8961797 ]
  • Pontifex MB, Raine LB, Johnson CR, Chaddock L, Voss MW, Cohen NJ, Kramer AF, Hillman CH. Cardiorespiratory fitness and the flexible modulation of cognitive control in preadolescent children. Journal of Cognitive Neuroscience. 2011; 23 (6):1332–1345. [ PubMed : 20521857 ]
  • Pontifex MB, Scudder MR, Drollette ES, Hillman CH. Fit and vigilant: The relationship between sedentary behavior and failures in sustained attention during preadolescence. Neuropsychology. 2012; 26 (4):407–413. [ PMC free article : PMC3390762 ] [ PubMed : 22746307 ]
  • Pontifex MB, Saliba BJ, Raine LB, Picchietti DL, Hillman CH. Exercise improves behavioral, neurophysiologic, and scholastic performance in children with ADHD. Journal of Pediatrics. 2013; 162 :543–551. [ PMC free article : PMC3556380 ] [ PubMed : 23084704 ]
  • Raji CA, Ho AJ, Parikshak NN, Becker JT, Lopez OL, Kuller LH, Hua X, Leow AD, Toga AW, Thompson PM. Brain structure and obesity. Human Brain Mapping. 2010; 31 (3):353–364. [ PMC free article : PMC2826530 ] [ PubMed : 19662657 ]
  • Rasberry CN, Lee SM, Robin L, Laris BA, Russell LA, Coyle KK, Nihiser AJ. The association between school-based physical activity, including physical education, and academic performance: A systematic review of the literature. Preventive Medicine. 2011; 52 (Suppl 1):S10–S20. [ PubMed : 21291905 ]
  • Raz N. Aging of the brain and its impact on cognitive performance: Integration of structural and functional findings. In: Craik FM, Salthouse TA, editors. In The handbook of aging and cognition. Vol. 2. Mahweh, NJ: Lawrence Erlbaum Associates; 2000. pp. 1–90.
  • Reed JA, Einstein G, Hahn E, Hooker SP, Gross VP, Kravitz J. Examining the impact of integrating physical activity on fluid intelligence and academic performance in an elementary school setting: A preliminary investigation. Journal of Physical Activity and Health. 2010; 7 (3):343–351. [ PubMed : 20551490 ]
  • Ruiz JR, Ortega FB, Castillo R, Martin-Matillas M, Kwak L, Vicente-Rodriguez G, Noriega J, Tercedor P, Sjostrom M, Moreno LA. Journal of Pediatrics. 2010; 157 (6):917–922. [ PubMed : 20673915 ]
  • Sallis JF, McKenzie TL, Kolody B, Lewis M, Marshall S, Rosengard P. Effects of health-related physical education on academic achievement: Project SPARK. Research Quarterly for Exercise and Sport. 1999; 70 (2):127–134. [ PubMed : 10380244 ]
  • Sanders A. Towards a model of stress and human performance. Acta Psychologica. 1983; 53 (1):61–97. [ PubMed : 6869047 ]
  • Shephard RJ. Habitual physical activity and academic performance. Nutrition Reviews. 1986; 54 (4):S32–S36. [ PubMed : 8700451 ]
  • Shephard RJ, Volle M, Lavallee H, LaBarre R, Jequier J, Rajic M. In Children and Sport. Berlin, Germany: Springer-Verlag; 1984. Required physical activity and academic grades: A controlled study; pp. 58–63.
  • Sibley BA, Etnier JL. The relationship between physical activity and cognition in children: A meta-analysis. Pediatric Exercise Science. 2003; 15 :243–256.
  • Silliker SA, Quirk JT. The effect of extracurricular activity participation on the academic performance of male and female high school students. School Counselor. 1997; 44 (4):288–293.
  • Singh A, Uijtdewilligen L, Twisk JWR, van Mechelen W, Chinapaw MJM. Physical activity and performance at school: A systematic review of the literature including a methodological quality assessment. Archives of Pediatrics and Adolescent Medicine. 2012; 166 (1):49–55. [ PubMed : 22213750 ]
  • Sirin SR. Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research. 2005; 75 (3):417–453.
  • Smith PJ, Blumenthal JA, Hoffman BM, Cooper H, Strauman TA, Welsh-Bohmer K, Browndyke JN, Sherwood A. Aerobic exercise and neuro-cognitive performance: A meta-analytic review of randomized controlled trials. Psychosomatic Medicine. 2010; 72 (3):239–252. [ PMC free article : PMC2897704 ] [ PubMed : 20223924 ]
  • Stanca L. The effects of attendance on academic performance: Panel data evidence for introductory microeconomics. Journal of Economic Education. 2006; 37 (3):251–266.
  • Stephens LJ, Schaben LA. The effect of interscholastic sports participation on academic achievement of middle level school activities. National Association of Secondary School Principals Bulletin. 2002; 86 :34–42.
  • Stewart JA, Dennison DA, Kohl HW III, Doyle JA. Exercise level and energy expenditure in the TAKE 10! ® in-class physical activity program. Journal of School Health. 2004; 74 (10):397–400. [ PubMed : 15724566 ]
  • Strong WB, Malina RM, Blimkie CJ, Daniels SR, Dishman RK, Gutin B, Hergenroeder AC, Must A, Nixon PA, Pivarnik JM, Rowland T, Trost S, Trudeau F. Evidence based physical activity for school-age youth. Journal of Pediatrics. 2005; 146 (6):732–737. [ PubMed : 15973308 ]
  • Taliaferro LA, Rienzo BA, Donovan KA. Relationships between youth sport participation and selected health risk behaviors from 1999 to 2007. Journal of School Health. 2010; 80 (8):399–410. [ PubMed : 20618623 ]
  • Taylor MJ. Neural bases of cognitive development. In: Bialystok E, Craik FIM, editors. In Lifespan cognition: Mechanisms of change. Oxford, UK: Oxford University Press; 2006. pp. 15–26.
  • Telama R, Yang X, Laakso L, Viikari J. Physical activity in childhood and adolescence as predictor of physical activity in young adulthood. American Journal of Preventive Medicine. 1997; 13 (4):317–323. [ PubMed : 9236971 ]
  • Thomas AG, Dennis A, Bandettini PA, Johansen-Berg H. The effects of aerobic activity on brain structure. Frontiers in Psychology. 2012; 3 :1–9. [ PMC free article : PMC3311131 ] [ PubMed : 22470361 ]
  • Tomporowski PD. Effects of acute bouts of exercise on cognition. Acta Psychologica. 2003; 112 (3):297–324. [ PubMed : 12595152 ]
  • Tomporowski PD, Davis CL, Miller PH, Naglieri JA. Exercise and children's intelligence, cognition, and academic achievement. Educational Psychology Review. 2008a; 20 (2):111–131. [ PMC free article : PMC2748863 ] [ PubMed : 19777141 ]
  • Tomporowski PD, Davis CL, Lambourne K, Gregoskis M, Tkacz J. Task switching in overweight children: Effects of acute exercise and age. Journal of Sport and Exercise Psychology. 2008b; 30 (5):497–511. [ PMC free article : PMC2705951 ] [ PubMed : 18971509 ]
  • Trudeau F, Shephard RJ. Physical education, school physical activity, school sports and academic performance. International Journal of Behavioral Nutrition and Physical Activity. 2008; 5 [ PMC free article : PMC2329661 ] [ PubMed : 18298849 ]
  • Trudeau F, Shephard RJ. Relationships of physical activity to brain health and the academic performance of school children. American Journal of Lifestyle Medicine. 2010; 4 :138–150.
  • Trudeau F, Laurencelle L, Tremblay J, Rajic M, Shephard R. Daily primary school physical education: Effects on physical activity during adult life. Medicine and Science in Sports and Exercise. 1999; 31 (1):111. [ PubMed : 9927018 ]
  • Trudeau F, Shephard RJ, Arsenault F, Laurencelle L. Changes in adiposity and body mass index from late childhood to adult life in the Trois-Rivières study. American Journal of Human Biology. 2001; 13 (3):349–355. [ PubMed : 11460900 ]
  • Trudeau F, Laurencelle L, Shephard RJ. Tracking of physical activity from childhood to adulthood. Medicine and Science in Sports and Exercise. 2004; 36 (11):1937. [ PubMed : 15514510 ]
  • Van Dusen DP, Kelder SH, Kohl HW III, Ranjit N, Perry CL. Associations of physical fitness and academic performance among schoolchildren. Journal of School Health. 2011; 81 (12):733–740. [ PubMed : 22070504 ]
  • Van Praag H, Kempermann G, Gage FH. Running increases cell proliferation and neurogenesis in the adult mouse dentate gyrus. Nature Neuroscience. 1999; 2 (3):266–270. [ PubMed : 10195220 ]
  • Voss MW, Chaddock L, Kim JS, VanPatter M, Pontifex MB, Raine LB, Cohen NJ, Hillman CH, Kramer AF. Aerobic fitness is associated with greater efficiency of the network underlying cognitive control in preadolescent children. Neuroscience. 2011; 199 :166–176. [ PMC free article : PMC3237764 ] [ PubMed : 22027235 ]
  • Wechsler H, Brener ND, Kuester S, Miller C. Food service and food and beverage available at school: Results from the School Health Policies and Programs Study. Journal of School Health. 2001; 71 (7):313–324. [ PubMed : 11586874 ]
  • Welk GJ, Jackson AW, Morrow J, James R, Haskell WH, Meredith MD, Cooper KH. The association of health-related fitness with indicators of academic performance in Texas schools. Research Quarterly for Exercise and Sport. 2010; 81 (Suppl 2):16S–23S. [ PubMed : 21049834 ]
  • Welk GJ, Going SB, Morrow JR, Meredith MD. Development of new criterion-referenced fitness standards in the Fitnessgram ® program. American Journal of Preventive Medicine. 2011; 41 (2):6. [ PubMed : 21961614 ]
  • Wilkins J, Graham G, Parker S, Westfall S, Fraser R, Tembo M. Time in the arts and physical education and school achievement. Journal of Curriculum Studies. 2003; 35 (6):721–734.
  • Wittberg R, Cottrell LA, Davis CL, Northrup KL. Aerobic fitness thresholds associated with fifth grade academic achievement. American Journal of Health Education. 2010; 41 (5):284–291.
  • Yeung N, Botvinick MM, Cohen JD. The neural basis of error detection: Conflict monitoring and the error-related negativity. Psychological Review. 2004; 111 (4):931. [ PubMed : 15482068 ]
  • Zhu W, Welk GJ, Meredith MD, Boiarskaia EA. A survey of physical education programs and policies in Texas schools. Research Quarterly for Exercise and Sport. 2010; 81 (Suppl 2):42S–52S. [ PubMed : 21049837 ]
  • Cite this Page Committee on Physical Activity and Physical Education in the School Environment; Food and Nutrition Board; Institute of Medicine; Kohl HW III, Cook HD, editors. Educating the Student Body: Taking Physical Activity and Physical Education to School. Washington (DC): National Academies Press (US); 2013 Oct 30. 4, Physical Activity, Fitness, and Physical Education: Effects on Academic Performance.
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JOURNAL OF PHYSICAL

Education research, issn online                                :   2394-4056, issn print                                   :   2394-4048, issn online     :     2394-4056, issn print        :     2394-4048, bring out the latest developments in the field of physical education, plant, animal and environmental sciences.

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Journal of Physical Education Research (JOPER) is a scientific publication. It is a peer reviewed and referred journal, officially publishes original research articles on Physical Education and its allied sciences. The JOPER is an open access international journal has four annual issues (March, June, September and December), with its own issue number and supplements if necessary for each issue. JOPER publishes in both printed and online version. It is devoted to the promotion of physical education and allied sciences. The experiences of different countries are very important to share on a platform like this. Therefore, this international journal serves to bring scholars from diver's background interns of their domain of specialization and scholarships and will enrich our understanding of various issues related to the physical education and sports. It also provides an International forum for the communication and evaluation of data, methods and findings in physical education and allied sciences. Based on the international character of the Journal, the articles/research papers can be published by authors from all over the world. The journal is under the indexing phase in several international bodies and organizations. The journal publishes scientific publications according to the criteria listed in the Guidelines for the Authors. Everyone who has met the requirements of the journal and who takes full responsibility for all that is written in the publication has the right to publish their article with us. The review and the corrections made by the editorial board and its associates do not dismiss the author (the co-authors) from the responsibility for his/her publication, and they also do not change its originality.

JOPER welcomes research articles from physical educators, sports scientists, health educators, coaches, athlete trainers and research scholars profoundly involved in physical education researches from all over the world to report their research findings and experiences with us. Applications of the publications are open throughout the year.

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Journal of Teaching in Physical Education

Indexed in: Web of Science, Scopus, PubMed/MEDLINE, ProQuest, APA PsycINFO, EBSCOhost, ERIC, Google Scholar

Print ISSN:  0273-5024             Online ISSN:  1543-2769

Cover Journal of Teaching in Physical Education

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Free access Principal Perceptions and Applications of Professional Learning Communities: Implications for the Future of Physical Education Authors: Zack E. Beddoes and Debra S. Sazama Free access Career Transitions: Decision-Making Dynamics Regarding Physical Education Teacher Education Doctoral Program Applications and Entry Authors: Kevin Patton and Melissa Parker

Volume 43 (2024): issue 1 (jan 2024).

  • Principal Perceptions and Applications of Professional Learning Communities: Implications for the Future of Physical Education
  • Encouraging Students to Co-Construct and Co- and Self-Regulate Their Learning Within a Cooperative Learning Environment in Physical Education
  • Recycling and Resistance to Change in Physical Education: The Informal Recruitment of Physical Education Teachers in Schools
  • Strength and Conditioning in U.S. Schools: A Qualitative Investigation of Physical Educators’ Socialization and Professional Experiences
  • The Relationship and Effect Among Physical Literacy Attributes in University Physical Education During the Pandemic Quarantine Period
  • Evaluating the Feasibility of the Education, Movement, and Understanding (EMU) Program: A Primary School-Based Physical Education Program Integrating Indigenous Games Alongside Numeracy and Literacy Skills
  • “From a Learning Perspective, It’s a Better Way for Them to Learn”: Impact of an Education Program on Two Youth Soccer Coaches’ Perspectives and Practices
  • The Ableist Underpinning of Normative Motor Assessments in Adapted Physical Education
  • The Effect of Classroom-Based Physical Activity Elements on Academic Performance in Children and Adolescents: A Meta-Analysis
  • Adopting Instructional Models in Physical Education: The Influence of Occupational Socialization
  • Examining the Knowledge and Training of Secondary School Physical Educators Providing Strength and Conditioning Programming
  • School–University Partnered Before-School Physical Activity Program: Experiences of Preservice Teachers, Program Facilitators, and Students
  • The Dissemination and Implementation of Recess Guidelines, Policies, and Practices During the COVID-19 Pandemic
  • An Analysis of Physical Education and Health Education Teacher Education Programs in the United States
  • A Whole-of-School Approach to Physical Activity Promotion: The Case of One Secondary School in England
  • How Movement Habits Become Relevant in Novel Learning Situations
  • Quality of Life in Individuals With Disabilities Through a Student-Led Service-Learning Program: Qualitative and Quantitative Analysis to Examine the Reciprocal Benefits of Service Learning
  • “It’s Like Coming Out of the Cave Into the Light”: The Role of Literacy Integration in Physical Education
  • Female Undergraduate Students’ Experiences Facilitating an Out-of-School Physical Activity Program for Middle School Girls
  • Assessing Student Ratings of Developmental Experiences in a High School Physical Education Leadership Program
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  • /journals/jtpe/34/1/jtpe.34.issue-1.xml Pages: 1–161
  • /journals/jtpe/33/3/jtpe.33.issue-3.xml Pages: 301–431

JTPE 2022 JIF: 2.8

JTPE is published quarterly in January, April, July, and October.

The purpose of the Journal of Teaching in Physical Education is to communicate national and international research and stimulate discussion, study, and critique of teaching, teacher education, and curriculum as these fields relate to physical activity in schools, communities, higher education, and sport. The journal publishes original reports of empirical studies in physical education together with integrative reviews and analyses of educational and methodological issues in the field. Research using a variety of methodological approaches is acceptable for publication. Well-designed replication of previous research is also strongly encouraged. Brief research notes also will be reviewed for possible publication. The coeditors and editorial board encourage the submission of manuscripts that extend knowledge within the focus of the journal.

Specific questions about the appropriateness of any individual paper to enter the JTPE peer-review process should be directed to one of the coeditors. Except for occasional invited manuscripts, all published articles are refereed by members of the editorial board, or by other referees invited by the coeditors. The final decision on whether a paper merits publication is made by the coeditor coordinating the review process.

Ethics Policy

Please visit the Ethics Policy page for information about the policies followed by JTPE.

Additional Content

Honoring Daryl Siedentop's contributions to JTPE: https://journals.humankinetics.com/page/Tribute-Daryl-Siedentop

Interested in being a reviewer for JTPE? Please fill out the JTPE Online Reviewer Form .

Heather Erwin University of Kentucky, USA

Incoming Editor

Kevin Andrew Richards University of Illinois Urbana-Champaign, USA

Editors Emeriti

Michael W. Metzler (Founding Editor: 1981–1987) Mark Freedman (Founding Editor: 1981–1984) Thomas J. Templin (1984–1988) David Griffey (1986–1989) Thomas J. Martinek (1988–1991) Judith Rink (1989–1992) Stephen Silverman (1991–1994) Mary O’Sullivan (1993–1996) Nell Faucette (1994–1998) Patt Dodds (1996–2000) Hans van der Mars (1998–2002) Deborah Tannehill (2000–2004) Bonnie Tjeerdsma Blankenship (2002–2006) Melinda Solmon (2004–2008) Ron McBride (2006–2010) Ping Xiang (2008–2012) Pamela Hodges Kulinna (2010–2014) Ben Dyson (2012–2016) Weidong Li (2014–2018) Mark Byra (2016–2020) Bryan McCullick (2018–2022)

Associate Editors

Erin E. Centeio University of Hawaiʻi at Mānoa, USA

Sara Flory University of South Florida, USA

Karen Gaudreault University of New Mexico, USA

Michael Hemphill University of North Carolina-Greensboro, USA

Risto Marttinen George Mason University, USA

Collin Webster University of Birmingham, Dubai, UAE

Tao Zhang University of North Texas, USA

Editorial Board

Laura Alfrey, Monash University, Australia

Dominique Banville, George Mason University, USA

Eve Bernstein, Queens College - CUNY , USA

Antonio Calderón, University of Limerick, Ireland

Weiyun Chen, University of Michigan, USA

Donetta Cothran, Indiana University, USA

Matthew Curtner-Smith, University of Alabama, USA

Ben Dyson, University of North Carolina, Greensboro, USA

Eimear Enright, University of Queensland, Australia

Tim Fletcher, Brock University, Canada

Alex Garn, Louisiana State University, USA

Tan Leng Goh, Central Connecticut State University, USA

Peter A. Hastie, Auburn University, USA

Pamela Hodges Kulinna, Arizona State University, USA

Cassandra Iannucci, Deakin University, Australia

Peter Iserbyt, KU Leuven, Belgium

Weidong Li, Ohio State University, USA

Ken Lodewyk, Brock University, Canada

Bryan McCullick, University of Georgia, USA

Scott McNamara, University of New Hampshire, USA

Geoff Meek, Bowling Green State University, USA

Thomas Quarmby, Leeds Beckett University, UK

Fernando Santos, Polytechnic Institute of Porto, School of Higher Education, Portugal

Bo Shen, Wayne State University, USA

Victoria (Tori) Shiver, University of New Mexico, USA

Mara Simon, Springfield College, USA

Kelly Simonton, University of Wyoming, USA

Oleg Sinelnikov, University of Alabama, USA

Suzan F. Smith-Ayers, Western Michigan University, USA

Melinda Solmon, Louisiana State University, USA

Michalis Stylianou, University of Queensland, Australia

Sue Sutherland, The Ohio State University, USA

Tristan Wallhead, University of Wyoming, USA

Jennifer Walton-Fisette, Kent State University, USA

Yubing Wang, University of Wisconsin-Whitewater, USA

Phillip Ward, The Ohio State University, USA

John Williams, University of Canberra, Australia

Wesley Wilson, University of Utah, USA

Ping Xiang, Texas A&M University, USA

Xihe Zhu, Old Dominion University, USA

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Paul Malinowski, University of Illinois at Urbana-Champaign, USA

Human Kinetics Staff Tammy Miller, Senior Journals   Managing Editor

Prior to submission, please carefully read and follow the submission guidelines detailed below. Authors must submit their manuscripts through the journal’s ScholarOne online submission system. To submit, click the button below:

Submit a Manuscript

Authorship Guidelines

The Journals Division at Human Kinetics adheres to the criteria for authorship as outlined by the International Committee of Medical Journal Editors*:

Each author should have participated sufficiently in the work to take public responsibility for the content. Authorship credit should be based only on substantial contributions to:

a. Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND b. Drafting the work or revising it critically for important intellectual content; AND c. Final approval of the version to be published; AND d. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Conditions a, b, c, and d must all be met. Individuals who do not meet the above criteria may be listed in the acknowledgments section of the manuscript. * http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html

Authors who use artificial intelligence (AI)-assisted technologies (such as Large Language Models [LLMs], chatbots, or image creators) in their work must indicate how they were used in the cover letter and the work itself. These technologies cannot be listed as authors as they are unable to meet all the conditions above, particularly agreeing to be accountable for all aspects of the work.

Open Access

Human Kinetics is pleased to allow our authors the option of having their articles published Open Access. In order for an article to be published Open Access, authors must complete and return the Request for Open Access form and provide payment for this option. To learn more and request Open Access, click here .

Manuscript Guidelines

All Human Kinetics journals require that authors follow our manuscript guidelines in regards to use of copyrighted material, human and animal rights, and conflicts of interest as specified in the following link: https://journals.humankinetics.com/page/author/authors

In preparing articles for submission to the Journal of Teaching in Physical Education , authors must follow the Publication Manual of the American Psychological Association (7th ed., 2020).

All articles must include an abstract of 100–150 words typed on a separate page along with three to six key words not used in the title. When submitting, you will be prompted to fill in the abstract in a specific box. Please also include the abstract in the manuscript file that is uploaded. JTPE editorial personnel request that a structured abstract format is used that includes labeling the following sections within the abstract paragraph: Purpose, Method, Results, and Discussion/Conclusion. Non-traditional papers (e.g., photovoice, reviews, position papers) may use other labeling systems. The entire manuscript must be double-spaced. Line numbers should be inserted, continuous throughout the text, to facilitate the review process. Tables must be prepared using Microsoft Word’s table-formatting functions. Manuscripts should be no longer than 30 total pages, inclusive of title page, abstract pages, main text, references, figures, and tables. Occasionally, the journal editors will consider longer submissions, but authors are asked to request editorial approval before submitting papers longer than 30 pages. Special attention should be given to the accuracy of the references and APA style. Figures must be crisp, clear, and properly labeled. Do not submit low-resolution electronic files. Manuscripts should not be submitted to another journal at the same time. All quantitative studies must report effect sizes. To facilitate blind review, the first page of the manuscript should include only the title of the manuscript and the date of submission. The manuscript itself should contain no clues as to the author’s identity. A separate cover sheet with contact information is no longer required because the necessary identifying information is entered when registering with the online submission system.

Manuscripts will be acknowledged upon receipt and will be sent to two reviewers for blind review; the review process normally takes two to three months for an initial decision. Once the manuscript has been accepted, it will be published in the first available space after the final revision has been received. There are no page charges to authors. 

Manuscript Submission Template

Authors are welcome to make use of this manuscript template to help ensure that their submission is consistent with JTPE 's formatting and author guidelines. However, this is not a requirement and authors are free not to use the template if that is preferred.

Guidelines for Replication Studies

Makel and Plucker (2014) proposed that replication is a powerful avenue to accumulate understanding by checking the validity of knowledge from previous research and enables questions concerning generalization across populations or contexts. Schmidt (2009) suggests that there are two primary forms of replication studies. The first includes "operational" replications that test the validity of the original data using similar procedures and research designs. The second are "constructive" replications, which attempt to replicate a research finding with different situations and different subjects, to determine if the basic findings of the original study can be applied to other participants and circumstances and is therefore linked to the wider notion of replication. In addition to the Manuscript Guidelines listed above, any Replication study submitted to JTPE must fall into one of these two categories. 

Makel, M.C., & Plucker, J.A. (2014). Facts are more important than novelty: Replication of the education sciences. Educational Researcher , 43 , 304–316. Schmidt, S. (2009). Shall we really do it again? The powerful concept of replication is neglected in the social sciences. Review of General Psychology , 13 , 90–100. 

Guidelines for Research Notes

Research Notes submitted to JTPE should meet the following guidelines:

Research Notes may consist of replication studies, data re-analyses studies, validation studies of existing instruments, and comments and dialogues on previously published papers. Manuscripts should use 12-point Times New Roman font and should be double-spaced (as per APA guidelines), with length not exceeding 14 pages, including text, references, tables, and figures. Consecutive line numbers should be inserted throughout the text to facilitate the review process. Submissions must include an abstract of 150 words or less. Research Notes should conform to the Publication Manual of the American Psychological Association (7th ed., 2020).

Review and Publishing Process

Research Notes follow the same review and publishing process as regular manuscripts.

Guidelines for Book Reviews

The Journal of Teaching in Physical Education is committed to publishing reviews of recent books that contribute to physical education, physical education teacher education, and related fields. In some instances, the book review editor may identify books worthy of review and ask scholars to author a book review. In other instances, scholars may propose to review a book based on their interest and expertise. Prospective book review authors should first contact the section editor to discuss their interest and ensure that the book they wish to review is a fit for JTPE and is not already under review.  The current book review section editor is Dr. Michael Hemphill ( [email protected] ).

Review Format

Book review authors should follow the Publication Manual of the American Psychological Association (7th edition, 2020) guidelines for journal article style. Keep references to a minimum. Check for the correct spelling of proper names. Check quotations for accuracy and make sure to provide page numbers for quotes. Reviews should be approximately 1,500 to 1,800 words. The text, including quotes and bibliographic information, should be double-spaced.

Bibliographic information for the book should be placed at the top of the review in the following format:

Title By Author(s). Publisher, year of publication, location of publisher, price, number of pages, ISBN. Reviewed by: Reviewer, institutional affiliation, location.

For example:

Reconceptualizing Physical Education: A Curriculum Framework for Physical Literacy, by Ang Chen. Routledge, 2022, New York, NY, $136, 276 pp., 9780367756949. Reviewed by: Michael Hemphill, University of North Carolina at Greensboro, Greensboro, NC.

Review Content

Book reviews should be relevant to readers of JTPE and be consistent with its mission to “stimulate discussion, study, and critique of teaching, teacher education, and curriculum as these fields relate to physical activity in schools, communities, higher education, and sport.” There are some books that would make an obvious fit to review for JTPE due to their purpose clearly relating to physical education. There may also be books from related areas that could be considered because they provide JTPE readers with insight into a topic of importance to our discipline. Prospective book review authors may contact the book review editor to discuss their interest in authoring a book review prior to committing to the project.

A good review provides description and analysis and attempts to situate a book in the larger scholarly conversation of the discipline. It is important to describe the author’s central thesis and the author’s approach to the text. The review should summarize the content and use examples to highlight key points; it should not be organized as a chapter-by-chapter synopsis of the book. Reviewers may choose to situate the book in relation to the author’s previous works, to scholarly debates in physical education or related areas, or to relevant literature in the field and particularly from JTPE . A constructive analysis of the book may include a summary of what makes it unique, strengths and weaknesses, the scope and relevance of its arguments, and/or its relationship to other published material. Book reviews often conclude by commenting on the book’s potential impact on the field, theoretical approach, or methodology. First-time reviewers are encouraged to read reviews that have appeared in other journals in related fields and from JTPE when possible.

Editorial Process

The submission of a review confirms that the review has not and will not appear elsewhere in published form. Book reviews will be received and edited by the Book Review Editor. Reviewers should note that the solicitation of a book review or the submission of an unsolicited review does not guarantee publication in the JTPE . Book review authors may be asked by the Book Review Editor to revise their reviews. The Book Review Editor makes recommendations for acceptance of reviews to the Editor of the journal. The Editor makes all final decisions about what will appear in the journal.

Acknowledgement

The guidelines for book reviews in JTPE were developed with insights from the book review section of the Sociology of Sport Journal .

Submitting a Manuscript

Manuscripts must be submitted through ScholarOne, the online submission system for the Journal of Teaching in Physical Education (see submission button at the top of this page). ScholarOne manages the electronic transfer of manuscripts throughout the article review process, providing systematic instructions and a user-friendly design. Please access the site and follow the directions for authors submitting manuscripts.

Any problems that might be encountered can be easily resolved by selecting “Help" in the upper-right corner of any ScholarOne screen. Authors of manuscripts accepted for publication must transfer copyright to Human Kinetics, Inc. This copyright agreement can be viewed by visiting the ScholarOne site and selecting "Instructions & Forms" in the upper-right corner.

JTPE is committed to mentoring young scholars to be able to conduct high-quality, timely peer reviews. We use a reviewer onboarding system in which reviewers may invite a graduate student or young scholar to review a manuscript to provide them with valuable training experience. Authors will have the option during manuscript subscription to decline to have their manuscript be part of this process.

Receiving a Decision

Effective July 1, 2019, JTPE  has implemented new decision categories for submitted manuscripts. To review these categories, see the document below.

  • JTPE Decision Categories

Guidelines for Monographs

Monograph proposals to JTPE should meet the following guidelines:

Manuscripts must use 12-point Times New Roman font (as per APA guidelines) and should be single-spaced, with length not exceeding 10 pages (including the overview but excluding the Appendix). Proposals should start with an overview chapter (Chapter 1), which clearly identifies the theme, scope, and need for the monograph. An overarching theoretical framework should inform the monograph. Individual chapters may also have additional/different theories that inform the work. Proposals should provide the abstracts for all chapters (6-10 chapters). Each chapter’s abstract should consist of the following elements: Title, Background, Purpose, Method, Data Analysis, Results, and Discussion/ Conclusions. Data should have already been collected at the time the proposal is submitted and results should be present in the proposal. Proposals should conform to the Publication Manual of the American Psychological Association (7th ed., 2020), except that the text should be single-spaced. Guest editors should be identified in the Appendix and serve as liaisons between chapter lead authors and JTPE coeditors. An Appendix should be submitted separately that provides the contact information of guest editors and the title of each of the chapters and its contributing authors with lead author contact information, along with an abbreviated CV (two pages) for each of the guest editors and lead authors. Proposals are due by July 31 of each year.

Review Process

All proposals are reviewed by a four-person review committee comprised of the two JTPE coeditors and two members of the JTPE editorial board.

Selection Process

The selection process is based on the following criteria: (a) relevance of topic and (2) quality of proposals, as determined by the four-person committee. Guest editors will be notified regarding the selection of monographs by September 15 of each year. If selected, guest editors must submit a complete monograph for further consideration in JTPE .

Publishing Process

The complete monograph is due three months after notification of selection (by December 15). Once received, the monograph will be reviewed by the four-person review committee through the online review process, with reviews sent only to the monograph guest editors. Henceforth, the review process continues following the standard JTPE format until the monograph is considered ready for publication or the monograph is rejected.

Guidelines for Special Issues

The following guidelines are intended to help scholars prepare a special issue proposal. Proposals on time-sensitive topics may be considered for publication as a special series at the Editor’s discretion. In no more than four pages, author(s) should address the following questions using the headings provided.

Synopsis  In 150 words or less, what is your special issue about? Important: Be sure to include its main themes and objectives. Rationale What are you proposing to do differently/more innovatively/better than has already been done on the topic (in JTPE specifically, as well as in the field more generally)? Why is now the time for a special issue on this topic? Why is JTPE the most appropriate venue for this topic? What are the main competing works on the topic (e.g., edited books, other special issues)? List up to five articles recently published on the topic that show breadth of scope and authorship in the topic. Qualifications Are you proposing to serve as Guest Editor for this special issue? If so, Please provide your vitae. Have you edited/co-edited a special issue before? If yes, please give the citation(s). Do you currently serve on any journal editorial boards? If yes, please list. If not, who do you suggest for a potential Guest Editor? Timeline Given that it takes approximately 12 months to complete a special issue, please provide a detailed timeline including estimated dates or time frames for the following steps: (a) Call for papers (b) Submission deadline (c) Review process (averages 4 months) (d) Revision process (averages 3 months) (e) Final editing and approval from JTPE editor (f) Completion and submission to Human Kinetics (must be at least 3 months prior to the issue cover month; e.g., completion by January 1 for the April issue)

Individuals

Online subscriptions.

Individuals may purchase online-only subscriptions directly from this website. To order, click on an article and select the subscription option you desire for the journal of interest (individual or student, 1-year or 2-year), and then click Buy. Those purchasing student subscriptions must be prepared to provide proof of student status as a degree-seeking candidate at an accredited institution. Online-only subscriptions purchased via this website provide immediate access to all the journal's content, including all archives and Ahead of Print. Note that a subscription does not allow access to all the articles on this website, but only to those articles published in the journal you subscribe to. For step-by-step instructions to purchase online, click here .

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Individuals wishing to purchase a subscription with a print component (print + online) must contact our customer service team directly to place the order. Click here to contact us!

Institutions

Institution subscriptions must be placed directly with our customer service team. To review format options and pricing, visit our Librarian Resource Center . To place your order, contact us . 

JTPE Editors and Reviewers Resource Center

Eligibility criteria and responsibilities of jtpe co-editors.

JTPE  co-editors are selected from the members of the editorial board. Upon selection, they serve as junior co-editor for a specified term of two years. Upon completion of this period, they serve as senior co-editor for another two-year term.

Eligibility Criteria Eligibility for  JTPE  co-editor appointments is based on the following criteria:

1. Co-editor candidates have published three manuscripts in the last five years in tier one journals (requirements: one publication in  JTPE  and one first authorship publication). 2. Co-editor candidates have demonstrated high-quality reviews in a timely manner while on the  JTPE  editorial board (a minimum of six reviews per year during the three-year term). 3. Co-editor candidates have served as  JTPE  editorial board members for six years (i.e., two terms) before selection.

  Responsibilities The  JTPE  co-editor responsibilities include, but are not limited to, the following:

1. Co-editors ensure the validity of the double-blinded review process. 2. Co-editors maintain confidentiality and objectivity regarding manuscripts and the review process. 3. The senior co-editor submits manuscripts to at least two reviewers expert in the specific area who can be objective and do not have conflicts of interest. In the case that the manuscript content or focus is inappropriate for  JTPE , the coeditors contact the author(s) rather than sending it out for review. 4. Co-editors correspond with authors and reviewers. 5. Co-editors make decisions regarding acceptance/rejection and resubmission/rejection of manuscripts based on reviewers’ feedback/recommendations.

To review more information on the duties of editors, including ethical responsibilities,  click here .

Nomination Process

Nominations for the co-editor positions originate from existing editorial board members and are submitted in writing to the senior co-editor who is responsible for contacting the nominees for their curriculum vitae and letter of interest, as well as for making arrangements for the selection process.

Co-editors are selected by current co-editors from the pool of  JTPE  editorial board members who meet the eligibility criteria and are interested in the position. The co-editors’ selection is ratified by the majority vote of the  JTPE  editorial board.

Co-Editor Publication Process

In the case a co-editor submits a manuscript for publication to  JTPE , the other co-editor assigns a guest co-editor to select reviewers and monitor the review process.

Editorial Board Members

Eligibility criteria and responsibilities for jtpe editorial board membership.

Editorial board members are appointed by the senior co-editor upon consensus of the editorial council (senior and junior co-editors).

Eligibility Criteria Eligibility for new board member appointments is based on the following criteria:

1. Potential editorial board member has obtained a doctoral degree specializing in sport pedagogy or related fields at least five years before serving on the  JTPE  editorial board. 2. Potential editorial board member has published three manuscripts in the last five years in tier one journals (initial membership requirements: one publication in  JTPE  and one first authorship publication). 3. Potential editorial board member has served as a guest reviewer for  JTPE  for one year and completed an adequate number of high-quality, non-biased reviews. 4. Potential editorial board member has demonstrated expertise in areas needed on the board. 5. Potential editorial board member is committed to attending the annual  JTPE  editorial board meetings when possible and to contributing to the mission of  JTPE .  

Responsibilities The members of the  JTPE  editorial board are appointed for three years and are directly accountable to the editors of  JTPE . In turn, the senior editor of  JTPE  is responsible to Human Kinetics, Inc. The  JTPE  editorial board members’ responsibilities include, but are not limited to, the following:

1. JTPE  editorial board members complete a minimum of six reviews per year in a timely manner. 2. JTPE  editorial board members provide respectful and constructive reviews for authors that avoid hurtful language and contribute to providing high-quality papers. 3. JTPE  editorial board members demonstrate confidentiality and objectivity regarding the manuscripts and the review process. 4. JTPE  editorial board members participate in the evaluation of the quality and effectiveness of JTPE to help maintain high standards.

Editorial board membership nominations are requested from existing  JTPE  editorial board members. Board members whose term has been completed and who wish to continue on the board can also nominate themselves as a self-nomination (through a letter of intent only). Nominations should be submitted in writing (preferably via electronic mail) to the senior editor, who is responsible for arranging the review/selection process. Nominees are then asked to submit a curriculum vita to the senior editor, along with a statement expressing their interest in the position and explaining their suitability.

The co-editors of  JTPE  will consider nominees who meet the eligibility criteria and have provided requested materials as potential  JTPE  editorial board members. The  JTPE  editorial board can consist of up to 32 members at a time.

Renewal of JTPE Editorial Board Membership

The co-editors determine the renewal of  JTPE  editorial board membership. Board members, upon completion of their term of service, are invited to continue to serve on the board if they have successfully fulfilled all their responsibilities during their three-year term. This will be determined by the eligibility criteria and their ability to fulfill appropriate responsibilities for  JTPE  editorial board membership.

Reviewer Guidelines

A. guidelines for the review of research-based manuscripts.

I. Appropriateness of Manuscript for  JTPE : The reviewer should comment on the appropriateness of the manuscript (refer to editorial policy of  JTPE ) based on the guidelines below (when they apply). Co-editors make final decisions about the appropriateness of manuscripts.

II. Relevance/Significance of the Study:

1. Is there a theoretical framework and/or is the study and the related construct(s) situated in the existing literature? 2. Is the theoretical framework logically explained or are the constructs tied together to explain how the research project was conceived? 3. Is the rationale for the study clear? 4. Does the literature review provide the most relevant and current scholarship on the topic that enriches an understanding of the theoretical framework or related constructs? 5. Are the purpose and the research questions derived from the literature review and are they consistent with the theoretical framework and/or the related constructs and rationale presented in the introduction? 6. Have the data been published elsewhere? 7. Are the interpretations based on valid, reliable, or trustworthy data/materials? 8. Has the work been sufficiently thorough to warrant publication? 9. What significant, unique, or valuable knowledge will readers learn from the study? 10. Overall, does the study add new knowledge and/or make a significant and/or a unique contribution to the existing literature base?

III. Methodology and Presentation of Results:

General Guidelines

1. Are the research questions specific enough so that the theoretical framework/construct logically leads to the selection of appropriate variables/phenomena for the investigation? 2. Is the research design explicitly explained? 3. Are participants clearly described? 4. Is information offered with regard to having obtained institutional approval and participants’ consent? 5. Are key characteristics of the participants provided? 6. Is the sequence of research procedure logical? 7. Are there sufficient data sources to address the research question(s)?

Guidelines for Quantitative Methods

1. Are variables operationally defined for data collection? 2. Is information about the validity and reliability of the measures reported? 3. Do the validity and reliability of the measures meet acceptable criteria? 4. Are control procedures described in experimental/quasi-experimental designs? 5. Are effective procedures used to minimize the threats to the validity and reliability of the measures? 6. Are statistical analyses compatible with or appropriate to the research questions? 7. Are advantages and disadvantages of using the analyses explained? 8. Were adequate assumptions for the statistical analyses examined and results reported? 9. Were descriptive statistics for the variables (dependent variables in particular) reported? 10. Are the parameters/indexes chosen to report results appropriate (especially in multivariate analyses)? 11. Were results for tests of statistical significance accompanied by effect size indices? 12. Are there any indications of calculation errors? 13. When using single-subject designs, were data paths interpreted appropriately according to accepted visual analysis tactics?

Guidelines for Qualitative Methods

1. Is the type of inquiry and its associated paradigm/perspective specified? 2. Does the author reveal sufficient personal/professional subjectivity for readers to assess the degree of the researcher’s role in the study and influence on the data presented? 3. Is the description of context detailed so that readers can situate the study within its social and educational environment? 4. Are detailed descriptions of key informants provided? 5. Are data collection protocols described? 6. Are sufficient data sources used for an effective triangulation to make the case that the data are trustworthy and credible? 7. If limited data sources were used, were additional efforts made to gather sufficient in-depth information from the sources to address the research questions adequately? 8. Are approaches to establishing trustworthiness appropriate? 9. Are data analysis protocols carefully described to show that the themes/grounded theories have been derived in a logical way?

IV. Discussion and Interpretation:

1. Has the discussion/interpretation of results been linked to the theoretical framework and/or constructs and rationale presented in the introduction? 2. To what extent do the findings make unique contributions to the body of knowledge? 3. Are interpretations of the results based on the data and related to the literature? 4. Are there any indications of over- or under-generalization of the results? 5. To what extent have the results answered the research questions (completely, partially, or not at all)? 6. If there are any critical limitations of the study in any section (e.g., theoretical foundation, methodology, results, and/or discussion), how well has the author addressed them? 7. Are practical implications of the findings presented when appropriate? 8. Are similarities and differences with previous findings noted and discussed? 9. Are unexpected results acknowledged and discussed?

V. Clarity of Information Presentation and Writing:

1. Does the writing allow a clear, accurate, and concise presentation of information? Are the sections coherently connected? 2. Does the writing avoid redundancy? 3. Are concepts clearly defined and explained when they first appear in the manuscript? 4. Has technical jargon been avoided or kept to a minimum? 5. Is the general arrangement of the sections logical? 6. Is it a finished piece of work? 7. Are there inappropriate or missing sections/headers? 8. Does the manuscript conform to the Publication Manual of the American Psychological Association (6th ed., 2010)? 9. Does the abstract present all key components in the manuscript in a very concise manner? 10. Are tables and figures accurate, clear, and concise? 11. Do tables and figures present necessary information that contributes to the understanding of the text, rather than redundant information which duplicates what is already in the text? 12. Is the reference list accurate and do citations in the manuscript accurately match those in the references section? 13. Is the tone of reporting academically appropriate? 14. Is an overly emotional tone avoided? 15. Is the length of the manuscript reasonable? 16. If longer than 28 pages (8.5 x 11, size 12 font), can any part be condensed or omitted without jeopardizing the significance of the manuscript?

B. Guidelines for the Review of Manuscripts Pertaining to Theoretical, Philosophical, and/or Applied Issues of Professional Practice

I. Contribution to the Body of Knowledge/Professional Practice: 

1. Does the author address a significant issue that is relevant to the scope of the journal (teaching/learning in physical education)? 2. Is the most current relevant literature included in the review? 3. Are the arguments based on solid theoretical frameworks, philosophical foundations, and/or empirical evidence? 4. To what extent does the manuscript advance our understanding of the issue? 5. Has the work been sufficiently thorough to warrant publication? 6. Is the quality of the content sufficient to warrant publication?

II. Quality of Information Presentation:

1. Are themes and/or philosophical positions stated clearly? 2. Are appropriate transitions used between/among themes to build logical and compelling arguments? 3. Does the presentation help readers conceptualize issues and arguments effectively? 4. Is the manuscript logically organized to achieve a clearly stated purpose that is suited to this journal? 5. Is the information conceptually integrated and coherently presented?

III. Discussion or Interpretation of Ideas and Information:

1. Has the author built constructive arguments that advance theory, knowledge, and/or applications related to the scope of the journal (teaching/learning in physical education)? 2. Is relevant literature adequately critiqued and integrated into the arguments? 3. Are the arguments based on well-reasoned thoughts, rather than emotions? 4. Does the reasoning throughout the manuscript seem to be sound? 5. Are the conclusions consistent with the arguments developed or the empirical evidence reviewed? 6. Are practical implications of the arguments and/or ideas emphasized?

C. Guidelines for Reviewing Manuscripts the Second or Third Time:

1. All major concerns by reviewers and editors should be addressed in the first revision of a manuscript. 2. New major revisions should not be requested during the second or third revision of a manuscript unless a major change (e.g., new theoretical framework or revised analyses) requires further recommendations for changes. 3. Original reviewers should be employed in subsequent reviews unless the co-editor’s decision for the original manuscript is reject.

Guest Reviewers

Guest reviewers must have an earned doctoral degree specializing in sport pedagogy or related fields. Doctoral students (in the third year of their programs or beyond) may also participate as a  JTPE  guest reviewer under the supervision of their doctoral mentors.

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Physical Education Research Paper Topics

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In this guide on physical education research paper topics , we explore a wide range of subjects that delve into the field of physical education. Whether you’re a student studying education or a researcher in the field, this comprehensive list of topics is designed to inspire and guide you in your research endeavors. From examining the impact of physical activity on academic performance to analyzing the effectiveness of different teaching methods in physical education, these research paper topics offer a diverse range of areas to explore.

100 Physical Education Research Paper Topics

Exploring the diverse facets of physical education through research papers offers a unique opportunity to delve deeper into the field and contribute to the growing body of knowledge. To assist you in this endeavor, we have compiled a comprehensive list of physical education research paper topics. These topics span various areas of interest, from the impact of physical education on mental health to the integration of technology in physical education curricula. Each category contains 10 stimulating and thought-provoking physical education research paper topics, providing you with a wide range of options to explore and develop your research.

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Physical Education Curriculum and Instruction

  • The integration of technology in physical education curricula.
  • The impact of standardized testing on physical education programs.
  • Strategies for promoting inclusivity and diversity in physical education classes.
  • The role of assessment and feedback in enhancing student learning in physical education.
  • The effectiveness of different teaching methods in physical education.
  • Examining the relationship between physical education and academic performance.
  • Addressing gender disparities in physical education participation and achievement.
  • Incorporating cultural competency in physical education curricula.
  • The influence of teacher-student relationships on student engagement in physical education.
  • Exploring the role of outdoor education in physical education programs.

Physical Activity and Health

  • Investigating the effects of physical activity on mental health and well-being.
  • The relationship between physical activity and obesity rates among children and adolescents.
  • Analyzing the impact of physical activity on cardiovascular health.
  • Exploring the role of physical activity in reducing the risk of chronic diseases.
  • Investigating the psychological benefits of regular physical activity.
  • The impact of physical activity interventions on sedentary behavior.
  • Examining the relationship between physical activity and cognitive function.
  • Analyzing the influence of physical activity on sleep patterns.
  • Exploring the role of physical activity in promoting healthy aging.
  • Investigating the socio-economic factors influencing physical activity participation.

Sports Psychology and Performance

  • Understanding the psychological factors influencing sports performance.
  • Examining the role of motivation in sports participation and performance.
  • Analyzing the impact of imagery and visualization techniques on athletic performance.
  • Investigating the effects of stress and anxiety on sports performance.
  • Exploring the psychological benefits of team sports participation.
  • The influence of leadership styles on team cohesion and performance.
  • Analyzing the role of self-confidence in sports performance.
  • Understanding the psychological challenges faced by athletes with disabilities.
  • Investigating the relationship between personality traits and sports performance.
  • Exploring the effects of psychological interventions on sports performance enhancement.

Exercise Physiology and Biomechanics

  • Investigating the physiological adaptations to different types of exercise.
  • Analyzing the biomechanics of specific movements in sports and exercise.
  • Exploring the effects of different training modalities on muscle strength and endurance.
  • The role of nutrition in exercise performance and recovery.
  • Investigating the effects of high-intensity interval training on cardiovascular fitness.
  • Analyzing the biomechanical factors influencing running gait and performance.
  • Exploring the physiological responses to altitude training.
  • Investigating the effects of aging on exercise capacity and performance.
  • Analyzing the impact of environmental factors on exercise performance.
  • Understanding the role of genetics in exercise physiology and performance.

Adapted Physical Education

  • Examining the benefits and challenges of inclusive physical education programs.
  • The role of assistive technology in facilitating physical education for individuals with disabilities.
  • Investigating the effectiveness of adapted physical education interventions.
  • Exploring strategies for promoting social inclusion in adapted physical education.
  • Analyzing the impact of inclusive physical education on self-esteem and self-efficacy.
  • Understanding the experiences and perceptions of individuals with disabilities in physical education.
  • Investigating the role of community partnerships in supporting adapted physical education.
  • Examining the professional development needs of physical education teachers in inclusive settings.
  • Analyzing the influence of policy and legislation on the provision of adapted physical education.
  • Exploring the role of peer support in enhancing the participation of individuals with disabilities in physical education.

Physical Education Pedagogy and Teacher Training

  • Investigating the impact of professional development programs on physical education teacher effectiveness.
  • Exploring the use of technology in enhancing physical education pedagogy.
  • Analyzing the role of reflection and self-assessment in physical education teacher development.
  • Investigating the factors influencing physical education teacher job satisfaction.
  • Understanding the challenges faced by physical education teachers in multicultural classrooms.
  • Examining the relationship between teacher-student interaction and student engagement in physical education.
  • Exploring effective strategies for managing behavior in physical education classes.
  • Analyzing the impact of mentoring and coaching on physical education teacher development.
  • Investigating the influence of school climate on physical education teacher motivation and performance.
  • Exploring the integration of social-emotional learning in physical education curricula.

Physical Education Policy and Advocacy

  • Analyzing the impact of policy on the provision of physical education in schools.
  • Investigating the role of advocacy organizations in promoting quality physical education programs.
  • Understanding the factors influencing physical education policy adoption and implementation.
  • Examining the relationship between physical education policies and student health outcomes.
  • Analyzing the impact of budgetary constraints on the quality of physical education programs.
  • Investigating the role of community partnerships in supporting physical education initiatives.
  • Exploring strategies for promoting physical education policy reform.
  • Understanding the influence of parental involvement on physical education policy and practice.
  • Analyzing the effects of policy changes on physical education teacher preparation programs.
  • Investigating the perceptions and attitudes of stakeholders towards physical education policies.

Assessment and Evaluation in Physical Education

  • Analyzing the effectiveness of different assessment methods in physical education.
  • Investigating the use of technology in assessing physical education outcomes.
  • Exploring the role of self-assessment and peer assessment in physical education.
  • Understanding the challenges and opportunities of authentic assessment in physical education.
  • Analyzing the impact of assessment practices on student motivation and engagement in physical education.
  • Investigating the alignment between physical education curriculum, instruction, and assessment.
  • Exploring the role of formative assessment in enhancing student learning in physical education.
  • Understanding the influence of standardized testing on physical education assessment practices.
  • Investigating the relationship between assessment practices and equity in physical education.
  • Analyzing the use of data-driven decision-making in improving physical education programs.

Physical Education and Technology

  • Investigating the use of wearable devices in monitoring physical activity and fitness levels.
  • Exploring the impact of virtual reality and augmented reality in physical education.
  • Analyzing the role of mobile applications in promoting physical activity and health.
  • Understanding the benefits and challenges of online physical education courses.
  • Investigating the use of gamification in enhancing student engagement in physical education.
  • Exploring the influence of exergaming on physical activity participation.
  • Analyzing the effectiveness of technology-mediated feedback in physical education.
  • Investigating the role of social media in promoting physical activity and healthy lifestyles.
  • Understanding the integration of technology in physical education teacher preparation programs.
  • Exploring the ethical considerations of using technology in physical education.

Physical Education and Social Justice

  • Analyzing the relationship between physical education and social inequality.
  • Investigating the experiences and perceptions of marginalized groups in physical education.
  • Exploring strategies for promoting social justice in physical education curricula.
  • Understanding the role of physical education in fostering cultural competence and inclusion.
  • Investigating the impact of gender norms on physical education experiences.
  • Analyzing the influence of socioeconomic status on access to quality physical education.
  • Exploring the intersectionality of race, gender, and physical education experiences.
  • Investigating the role of physical education in promoting social-emotional well-being and resilience.
  • Analyzing the impact of inclusive policies and practices on social justice in physical education.
  • Understanding the challenges and opportunities of integrating social justice in physical education pedagogy.

research paper in physical education

The comprehensive list of physical education research paper topics presented here is just the beginning of your research journey. Delve into the categories, choose a topic that resonates with your interests, and embark on a fascinating exploration of the subject matter. Remember to consider the relevance, significance, and feasibility of your chosen topic, and conduct thorough research to develop a well-informed and insightful research paper. Whether you seek to uncover the benefits of physical activity or analyze the effectiveness of different teaching methods, these topics will inspire you to expand your understanding of physical education and contribute to the advancement of knowledge in the field.

Physical Education Research Guide

Welcome to the world of physical education research! This page serves as a valuable resource for students and researchers in the field of education who are eager to explore the realm of physical education through the lens of research papers. Physical education plays a vital role in promoting health, wellness, and overall development among individuals of all ages. It encompasses a wide range of physical education research paper topics, from the impact of physical activity on academic performance to the effectiveness of various teaching approaches in physical education.

The primary objective of this page is to provide you with a comprehensive overview of physical education research paper topics. By delving into these topics, you will gain a deeper understanding of the key issues, theories, and practices within the field. The list of topics is categorized into 10 distinct categories, each offering 10 diverse and thought-provoking research paper ideas. Whether you’re interested in exploring the role of technology in physical education or investigating the social and cultural aspects of sports, you’ll find a wealth of ideas to spark your curiosity and fuel your research journey.

In addition to the extensive list of research paper topics, this page also offers expert advice on how to choose the most appropriate topic for your research project. Selecting a compelling and relevant research topic is essential to ensure the success of your study. Our expert guidance will provide you with valuable insights and practical tips to help you navigate through the multitude of options and select a topic that aligns with your interests, research goals, and academic requirements.

Furthermore, we understand that crafting a research paper can be a challenging task. To support your academic journey, we offer custom writing services that allow you to order a personalized research paper on any physical education topic of your choice. Our team of expert degree-holding writers possesses the knowledge and expertise to deliver high-quality, well-researched papers that meet your specific needs. With our commitment to in-depth research, customized solutions, and adherence to formatting styles such as APA, MLA, Chicago/Turabian, and Harvard, we strive to provide you with a seamless and professional writing experience.

So, whether you’re a student embarking on a research project or a researcher seeking new avenues of exploration, this page is designed to inspire, inform, and empower you in your quest for knowledge in the field of physical education. Let us embark on this exciting journey together as we delve into the fascinating world of physical education research paper topics.

Choosing a Physical Education Topic

When it comes to choosing a research paper topic in the field of physical education, it is crucial to select a subject that aligns with your interests, addresses a relevant issue, and allows for meaningful exploration. To help you make an informed decision, here are ten expert tips on selecting the right physical education research paper topic:

  • Identify your passion : Consider the aspects of physical education that you find most fascinating and meaningful. Are you interested in exploring the impact of technology on physical education, the role of physical education in promoting mental health, or the relationship between physical activity and academic performance? By selecting a topic that aligns with your passion, you will be more motivated to dive deep into the research and produce an exceptional paper.
  • Stay updated with current literature : Regularly review the latest research articles, books, and journals in the field of physical education. This will help you identify emerging trends, controversial topics, and gaps in existing knowledge, enabling you to choose a research topic that is current and relevant.
  • Consider the target population : Physical education encompasses various age groups and populations, including children, adolescents, adults, and individuals with special needs. Reflect on which population interests you the most and tailor your research topic accordingly. For example, you may explore the effectiveness of physical education programs for children with disabilities or the impact of physical activity interventions on older adults’ well-being.
  • Delve into emerging areas : Explore emerging areas within physical education that are gaining attention, such as inclusive education, adaptive physical education, or the integration of technology in teaching and learning. By choosing a topic in these emerging areas, you can contribute to the advancement of knowledge in the field.
  • Address local or global issues : Consider researching topics that address local or global issues in physical education. For instance, you may examine the impact of socio-cultural factors on physical education participation rates in a specific community or analyze the effects of globalization on physical education curriculum development.
  • Consult with experts : Seek guidance from professors, academic advisors, or professionals in the field of physical education. They can provide valuable insights, suggest potential research topics, and help you narrow down your focus based on their expertise and experience.
  • Conduct a literature review : Before finalizing your research topic, conduct a comprehensive literature review to identify existing studies, theories, and gaps in knowledge. This will help you refine your research question and ensure that your topic contributes to the existing body of literature.
  • Consider research feasibility : Assess the availability of data sources, research methods, and potential challenges associated with your chosen topic. Ensure that you have access to relevant data, research participants (if applicable), and the necessary resources to carry out your study successfully.
  • Balance novelty and significance : Strive to find a balance between selecting a novel and unique topic while ensuring its significance within the field of physical education. Aim to choose a topic that adds value to the existing knowledge and has the potential to influence practice or policy in a meaningful way.
  • Reflect on personal and professional goals : Consider how your chosen research topic aligns with your personal and professional goals. Will it contribute to your academic and career development? Does it align with your long-term aspirations within the field of physical education? Selecting a topic that resonates with your goals will enhance your motivation and dedication throughout the research process.

Remember, the process of choosing a research paper topic in physical education is iterative. Be open to exploring different ideas, seeking feedback from experts, and refining your topic based on the available resources and research feasibility. By selecting a topic that aligns with your passion, addresses a relevant issue, and has the potential for significant impact, you will be well-equipped to embark on a successful research journey in the field of physical education.

How to Write a Physical Education Research Paper

Writing a research paper in the field of physical education requires careful planning, thorough research, and effective organization of ideas. Here are some essential steps to guide you through the process of writing a compelling and well-structured physical education research paper:

  • Understand the assignment : Familiarize yourself with the requirements and guidelines provided by your instructor or educational institution. Pay attention to the research question, formatting style, word count, and any specific instructions or expectations.
  • Conduct thorough research : Begin by conducting extensive research on your chosen topic. Utilize various sources such as academic journals, books, reputable websites, and databases to gather relevant and reliable information. Take detailed notes and ensure that you cite your sources accurately.
  • Develop a strong thesis statement : Formulate a clear and concise thesis statement that captures the main objective or argument of your research paper. The thesis statement should guide your research and provide a roadmap for the rest of your paper.
  • Outline your paper : Create a well-organized outline to structure your research paper. Divide it into sections such as introduction, literature review, methodology, findings, analysis, and conclusion. Outline the main points and supporting evidence you will include in each section.
  • Write a compelling introduction : Begin your paper with an engaging introduction that grabs the reader’s attention and provides background information on the topic. Clearly state the purpose of your research, introduce the key concepts, and present your thesis statement.
  • Conduct a comprehensive literature review : Dedicate a section of your paper to reviewing relevant literature on the topic. Summarize and analyze existing studies, theories, and perspectives related to your research question. Identify gaps in the literature that your research aims to address.
  • Describe your research methodology : Explain the research design, methods, and procedures you used to collect and analyze data. Provide a clear description of the participants, materials, and instruments used. Justify the appropriateness of your chosen methods for addressing your research question.
  • Present your findings : Share the results of your research in a clear and organized manner. Use tables, graphs, or charts to present quantitative data and provide detailed descriptions for qualitative data. Analyze and interpret the findings in relation to your research question.
  • Discuss the implications and significance : Analyze the implications of your findings and their significance in the field of physical education. Discuss how your research contributes to the existing knowledge, addresses the research question, and impacts practice or policy.
  • Conclude your paper effectively : Summarize the main points of your research paper in the conclusion section. Restate your thesis statement and highlight the key findings and implications. Discuss the limitations of your study and suggest areas for further research.
  • Revise and edit : Review your research paper thoroughly for clarity, coherence, and logical flow. Check for grammatical and spelling errors, and ensure proper citation of sources using the required formatting style.
  • Seek feedback : Before submitting your final paper, seek feedback from peers, professors, or mentors. Incorporate their suggestions and revisions to improve the overall quality of your research paper.

By following these steps and dedicating sufficient time to each stage of the writing process, you can produce a well-researched and well-structured physical education research paper that effectively contributes to the field.

Order a Custom Research Paper

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  • Expert degree-holding writers : Our team of writers consists of highly qualified professionals with advanced degrees in the field of education. They have extensive knowledge and experience in conducting research and writing academic papers, ensuring the highest quality of work.
  • Custom written works : We understand the importance of originality in academic writing. Each research paper we deliver is custom-written from scratch, tailored to your specific requirements and guidelines. Our writers conduct thorough research and utilize credible sources to ensure the uniqueness and authenticity of your paper.
  • In-depth research : Our writers have access to a wide range of academic resources and databases, enabling them to conduct in-depth research on your chosen topic. They will gather relevant and up-to-date information to support the arguments and claims in your research paper.
  • Custom formatting : Our writers are well-versed in various formatting styles commonly used in academic writing, including APA, MLA, Chicago/Turabian, and Harvard. They will ensure that your research paper adheres to the required formatting guidelines.
  • Top quality and customized solutions : We prioritize quality and strive to deliver research papers that meet the highest standards. Our writers pay attention to every detail of your requirements and instructions, ensuring a customized solution that reflects your unique perspective and academic level.
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  • Easy order tracking : Our user-friendly platform allows you to easily track the progress of your order. You can communicate directly with your assigned writer, providing clarifications or additional instructions as needed.
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research paper in physical education

ORIGINAL RESEARCH article

Exercise makes better mind: a data mining study on effect of physical activity on academic achievement of college students.

Shuang Du

  • 1 College of Language Intelligence, Sichuan International Studies University, Chongqing, China
  • 2 College of Teacher Education, Southwest University, Chongqing, China

The effect of physical activity (PA) on academic achievement has long been a hot research issue in physical education, but few studies have been conducted using machine learning methods for analyzing activity behavior. In this paper, we collected the data on both physical activity and academic performance from 2,219 undergraduate students (Mean = 19 years) over a continuous period of 12 weeks within one academic semester. Based on students’ behavioral indicators transformed from a running APP interface and the average academic course scores, two models were constructed and processed by CHAID decision tree for regression analysis and significance detection. It was found that first, to attain higher academic performance, it is imperative for students to not only exhibit exceptional activity regularity, but also sustain a reduced average step frequency; second, the students completing running exercise with an average frequency of 1 time/week and the duration of 16–25 min excelled over approximately 88 percentage of other students on academic performance; third, the processing validity and reliability of physical observation data in complex systems can be improved by utilizing decision tree as a leveraging machine learning tool and statistical method. These findings provide insights for educational practitioners and policymakers who will seek to enhance college students’ academic performance through physical education programs, combined with data mining methods.

Introduction

The relationship between physical activity and academic performance has been studied in various adolescent populations in different countries. For instance, data from public schools in the northeastern United States confirmed a positive correlation between physical fitness test scores and pass rates in math and English course assessments ( Chomitz et al., 2010 ). Moreover, middle school students who met the aerobic endurance running standards not only had a higher likelihood of meeting standardized test benchmarks but also demonstrated improved academic performance ( Bass et al., 2013 ). In Spain, after controlling for BMI z-scores, waist circumference, and body fat percentage, the levels of aerobic fitness and motor skills were positively correlated with the grades on math and language tests among 6–18-year-old adolescents ( Esteban-Cornejo et al., 2014 ). Similarly, in Japan, cardiorespiratory fitness and overall health-related fitness were found to have significant positive effect on academic performance among middle school students ( Ishihara et al., 2018 ). Meanwhile, in a study involving 183 college students examining the relationship between physical fitness and academic performance, it was found that, apart from body mass index (BMI), all students’ physical fitness tests showed a significant positive correlation with average academic scores, indicating that high levels of physical fitness contribute positively to academic success ( Başkurt et al., 2020 ). Zhang (2022) further investigated the factors influencing physical fitness scores among college students and identified physical fitness level, exercise frequency, and physical injuries as key factors. Currently, there is a contentious debate in the academic community regarding the apparent association between physical activity and academic performance due to varying research methodologies and data sources employed ( Rodriguez et al., 2020 ).

In addition to the correlation and predictability of physical exercise on academic performance, some previous research has incorporated social cognitive theories from psychology to explain the underlying mechanisms. This suggests that the enhancement of students’ cognitive abilities through physical activity primarily manifests in self-control, specifically focusing on self-regulatory efficacy ( Anderson et al., 2006 ). The impact of self-efficacy on self-regulation and its association with exercise are highlighted, with self-regulatory efficacy positively correlated with exercise intensity ( Bauman et al., 2012 ). This explanation aligns well with social cognitive theory, as identifying oneself as an exerciser is, to some extent, influenced by past exercise experiences and serves as a source of self-efficacy ( Bandura, 1997 ). Moreover, achieving the desired intensity of exercise is associated with various behavioral outcomes related to academic development ( Strachan and Whaley, 2013 ), including weekly exercise minutes ( Strachan et al., 2010 ), weekly exercise frequency, duration and intensity of vigorous exercise ( Strachan and Brawley, 2008 ), and the number of weeks engaging in exercise ( Anderson et al., 1998 ). These studies indicate a correlation between exercise intensity and self-regulation. Therefore, the question arises as to which specific aspect of cognitive processes in adolescents may be impacted by physical exercise and how exactly it influences cognition. Current research has only scratched the surface by exploring certain facets of cognitive processes, and the studies conducted thus far remain fragmented ( Balk and Englert, 2020 ).

In the study of the mechanisms underlying the impact of physical activity on academic performance, two approaches are commonly used: examining the mediating variables in the causal pathway between the two factors and exploring the underlying mechanisms from other disciplines such as psychology and cognitive science. The former approach, as proposed by Kayani et al. (2018) , was “physical activity → self-esteem → learning motivation and performance,” which suggests that the strongest mediator between physical activity and academic performance is self-esteem. To put it another way, physical activity could enhance students’ self-esteem, which may serve as a guarantee for their motivation and academic success. Liang and Li (2020) explored the pathway of “physical activity → physical health → academic performance” by considering both explicit physical appearance and implicit physical skills as mediating factors. The scholars underscored the pivotal role of physical fitness as a significant mediating factor influencing academic achievement ( Chacón-Cuberos et al., 2020 ; Koçak et al., 2021 ). The aforementioned studies illuminate the substantial correlation existing between psychological factors, physical well-being, and academic attainment. Specifically, factors such as self-control and low self-efficacy have been found to exert a significant influence on tendencies toward overeating, weight gain, and diminished physical fitness. As the volume of data utilized in sports research continues to grow, the expansive magnitude and complex nature of sports-related data necessitate enhanced data processing techniques.

In the field of sports research, there is an increasing inclination toward the utilization of non-linear data mining techniques. These approaches offer practical insights into associations between predictor variables (e.g., team performance indicators) and dependent variables (e.g., match outcomes) ( Robertson et al., 2016 ). Unlike linear methods, these approaches can reveal multiple patterns within the data ( Mandorino et al., 2021 ; Teixeira et al., 2022 ). One widely-used non-linear method is the decision tree, which partitions samples based on maximum information entropy ( Mooney et al., 2017 ). Hijriana and Muttaqin (2016) applied decision trees to classify academic achievement, while You et al. (2018) used them to analyze physical activity’s impact on hypertension prevention in middle-aged and older adults in China. Pei et al. (2019) evaluated five classifiers for identifying individuals with diabetes based on clinical features. Benediktus and Oetama (2020) employed the decision tree C5.0 classification algorithm, based on information entropy, to predict student academic performance and explore the role of student activeness as a predictor. The use of information entropy allows for a comprehensive exploration of intricate relationships and patterns within the complex system of physical activity ( Silva et al., 2016 ). In this study, information entropy was also employed to construct indicators of activity patterns, with the aim of quantitatively assessing the uncertainty and randomness in the exercise patterns and trends of college students.

The progression of research involving the CHAID (Chi-squared Automatic Interaction Detector) method, in contrast to the commonly used decision tree algorithm, can be traced through multiple studies. Sanz Arazuri and de Leon Elizondo (2010) initially elucidated the application of hierarchical segmentation with CHAID, laying the foundation. Subsequently, Gómez et al. (2015) employed CHAID to pinpoint influential variables in ball screens, demonstrating its practical use. Building on this, Robertson et al. (2016) delved deeper, revealing distinctions between teams and showcasing CHAID’s effectiveness in crafting performance indicator profiles. In a more recent study, Eagle et al. (2022) extended the research by utilizing CHAID for subgroup analysis and examining its role in assessing sport-related suicide risk. Throughout these studies, CHAID consistently displayed its potential in predicting behavior indicators and elucidating causal relationships, as underscored by Schnell et al. (2014) , thus emphasizing its evolving significance in the field.

In the realm of academic inquiry, a contentious debate persists regarding the connection between physical activity and academic performance. This debate stems from the diverse research methodologies and data sources employed in previous studies ( Rodriguez et al., 2020 ). Our research endeavors to contribute to this discourse by addressing several key objectives. Firstly, we aim to unravel the intricate relationship between physical activity and academic achievement among college students. we aspire to delve deeper into the impact of physical exercise on cognitive processes in adolescents. While prior research has touched upon this topic, our goal is to identify specific facets of cognition influenced by exercise intensity. Secondly, we recognize the need for advanced data processing techniques in sports research due to the complex and expansive nature of sports-related data. By embracing non-linear data mining methodologies and leveraging information entropy, we aim to offer a fresh approach to exploring intricate relationships and patterns within the realm of physical activity and its impact on academic achievement. Furthermore, we also aim to elucidate the interplay between psychological factors, physical well-being, and academic attainment. By focusing on variables such as self-control and self-efficacy, we intend to shed light on their significant influence on behaviors related to physical fitness. Our research seeks to provide a holistic perspective on student well-being and academic success. We focused on three principal research objectives:

• Q1: Is there a correlation between the data model constructed using behavioral indicators and academic performance?

• Q2: How can effectively uncover the factors that influence academic performance and attribute interpretability to physical activity metrics through the utilization of machine learning techniques?

• Q3: How can the establishment of a pathway depicting the factors of physical activity on academic performance aid in revealing the potential mechanisms?

Data source and preprocessing

The research data was gathered over a continuous 12-week period during one academic semester from undergraduate students at Sichuan International Studies University in China, with an average age of 19.08 years. The data was obtained from two different systems. Firstly, approximately 9,000 academic records, including the grades of three subjects and physical fitness test scores, were retrieved from the Educational Administration System. Secondly, the physical activity log data for the research subjects during the semester was extracted from a running app installed on their mobile phones, yielding approximately 34,000 records.

In the context of this study, the log data was distributed across various business systems, necessitating a series of preprocessing steps to fully harness the data’s intrinsic value when constructing predictive indicators. Initially, the log data undergone anonymization and aggregation, involving the removal of sensitive information such as names, ID numbers, and phone numbers, followed by the correlation and integration of multiple datasets. Subsequently, common issues associated with log data, such as missing and imbalanced data, were addressed. Specifically, post-aggregation data undergone cleansing and adjustments. For instance, approximately 3.5% of students lacked running data, and there existed an imbalance in the gender ratio at college (male-to-female ratio: 1:4.3). Hence, during the preprocessing stage, missing data were addressed by eliminating invalid and duplicate records. Additionally, for datasets exhibiting skewed distributions, a Stratified Sampling approach was employed for female students to reduce the sample size, while a Bootstrap method was applied to male students to augment the sample size. This adjustment resulted in a more balanced male-to-female student data ratio of approximately 1:1.5, ensuring the integrity and validity of the predictive dataset. Ultimately, following data processing, a sample of 2,129 students was retained for the purposes of this research.

Physical behavioral indicators

Behavioral indicators are input datasets used for machine learning modeling. Wearable sports monitoring devices or mobile apps are applied to quantify various parameters and indicators of individuals and even groups, such as movement trajectories, exercise habits, energy expenditure, and health status. There are two main types of behavioral indicators: demographic indicators and behavioral indicators. Demographic indicators include basic personal information about students, such as age, gender, and major, which have good predictive capabilities in the early stages of learning activities which represent static data ( Whitener, 1989 ). Behavioral indicators, on the other hand, encompass changing data generated during learning activities, such as activity frequency, duration and speed. These indicators exhibit better predictive effects in the middle and later stages of activities ( Hussain et al., 2018 ; Karthikeyan et al., 2020 ), representing dynamic data. The research primarily investigates students’ behavioral performance, specifically the impact of dynamic indicators on academic performance. Hence, in the construction of the analytical model, performance indicators pertaining to physical exercise are carefully chosen. Subsequently, directional indicators are employed to visually represent and classify the findings, thereby providing an effective means to elucidate the observed outcomes.

The utilization of information entropy in constructing an activity regularity indicator for college students aims to quantitatively measure the uncertainty and randomness pertaining to their exercise patterns and trends. Information entropy plays a vital role in the analysis of intricate systems in sports research, providing researchers with quantitative measures to assess and analyze various aspects of complex sports systems ( Rhea et al., 2011 ). For instance, the utilization of entropy measurements in team sports has exhibited considerable potential in evaluating the uncertainty pertaining to players’ spatial distributions, dominant regions, and various collective team behaviors ( Silva et al., 2016 ). Additionally, entropy has been employed to analyze the complexity and information content of heart rate variability as an indicator of activity ( Namazi, 2021 ). In this study, entropy measures have been employed in investigating the variability of performance to unveil the underlying interactions governing activity regulation among college students, and the indicator Hx was calculated based on the distribution of exercise frequency. The entropy value was computed using the proportion of the number of exercise sessions on days for one student out of the total number of exercise sessions over days. The Hx indicator codes and descriptions are presented in Table 1 .

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Table 1 . Descriptive characteristics of physical activity behavioral indicators and academic achievement indicators.

Physical behavioral indicators in current study were constructed based on the key indicators of the Physical Activity Readiness Questionnaire (PAR-Q). These indicators were developed from three aspects: exercise intensity, duration, and frequency ( Thomas et al., 1992 ; Liang, 1994 ; Shephard, 2015 ). PAR-Q is widely used to assess physical activity levels. By scoring the three dimensions in the questionnaire, the individual’s exercise volume is calculated using the formula “intensity * duration * frequency = exercise volume.” This study built exercise indicators reflecting students’ physical activity (running) over a 12-week period in one semester. These indicators included distance covered (in meters), average step frequency (steps per minute), average pace (meters per minute), running duration (in seconds), exercise regularity, and frequency. Among them, distance, step frequency, and pace reflected exercise intensity; running duration reflected exercise time; exercise regularity and frequency reflected exercise frequency. The specific indicator codes and descriptions are presented in Table 1 .

Academic achievement indicators

Academic performance (AP) indicators, are influenced by a number of factors such as teacher subjectivity, selection bias, and student behavior ( Marques et al., 2018 ). Scholars commonly employ standardized tests to assess AP. Examples include the Academic Aptitude Test (SAT) in the United States, the National High School Examination (ENEM) in Brazil, and the General Scholastic Ability Test (GSAT) for higher education admission in Taiwan. Some researchers also use final grades from common courses and major-specific courses within the students’ respective schools as indicators of academic performance. In the current study, the physical fitness scores and standardized average scores from major-specific courses of first-year university students over one semester were used as predictive targets to evaluate their physical fitness and academic performance. As for the selection of major-specific scores, due to the large sample size and the variation among students’ colleges and majors, AP was primarily determined by the average scores of their highest credit courses. The conversion method is detailed in Table 1 .

Data mining based on machine learning

In order to enhance the interpretability of the study’s predictions, the target variables for prediction were not the conventional classification categories such as “pass,” “good,” and “excellent,” but rather continuous variables directly associated with academic performance scores. This choice transformed the task into a typical regression problem. The study had two main parts: firstly, the data collected from the administration system and mobile apps are anonymized, aggregated, and cleaned, and the predictive variables for correlation and variance inflation factor (VIF) to identify the optimal predictors. Secondly, the CHAID decision tree algorithm was utilized for significance testing and branch prediction, providing statistical explanations and attributions to the results, and identifying potential factors influencing academic performance from the patterns of physical activity behavior among college students. The flowchart involving data collection, preprocessing, screening process, and data model construction, and CHAID decision tree modeling is shown in Figure 1 .

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Figure 1 . Flowchart of data mining based on physical activities.

To validate and compare the predictive capabilities of physical behavioral indicators on academic performance, the behavioral dataset was divided into two subsets. Both subsets were associated with the predictive target variables of academic performance, forming the learner data models Model 1 and Model 2, as follows. These data models served as the data source for subsequent prediction model construction and performance comparison.

Model 1: Physical behavioral indicators (Variables) - > Academic Performance Score (All Target).

Model 2: Physical behavioral indicators (Variables) - > Academic Performance Score (Only AP > 80).

Analysis tools

The predictive tools employed in this study utilized prediction algorithms provided by machine learning models, specifically SPSS Modeler for predictive modeling and analysis. The CHAID module in SPSS Modeler was used for decision tree visualization modeling. This module is used for branch prediction and significance analysis in the two data models. By utilizing the CHAID method, we could quickly and effectively unearth the primary influencing factors. This approach could handle nonlinear and highly correlated physical behavioral data. Furthermore, it could accommodate missing values, thus overcoming restrictions faced by traditional parametric tests in these aspects.

Correlation analysis

Correlation analysis and variance inflation factor (VIF) tests were conducted on the behavioral indicators. The former assessed the phenomenon correlation between the predictive indicators and the target variable, while the latter evaluated the collinearity among the indicators within a controllable range. If the VIF value was less than 0.1 or greater than 10, it indicated poor predictive performance and necessitates adjustment or removal of the respective indicator (as shown in Table 2 ). From Table 2 , it can be observed that the average running speed (S X ) has a relatively high VIF value, but it still falls within a reasonable range. All other indicator VIF values are less than 3, indicating that all predictive indicators satisfy the collinearity condition and should be retained.

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Table 2 . Descriptive statistics, correlations, and VIF between physical behavioral indicators and academic achievement indicators.

Impact of exercise performance indicators on academic performance from data model 1

The analysis of academic performance was conducted based on the indicators from data model 1, as shown in Figure 2 .

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Figure 2 . CHAID decision tree analysis diagram based on data model 1.

From Figure 2 , it is evident that exercise regularity significantly influences academic performance ( p  < 0.00). In Node 2, 70% of students exhibited exercise regularity ranging from 0.488 to 0.753. These students, as long as they maintain good exercise regularity, can achieve satisfactory academic performance (AP = 79.951, comparable to the overall average of 79.553). Within the subset of students with higher exercise regularity, some individuals (Node 6) not only demonstrate regular exercise habits but also fulfill the designated running distance (Dx > 2731.63), resulting in above-average scores (AP = 80.896). The highest score is observed in Node 7, where students with the best exercise regularity (Hx > 0.796) and not necessarily fast running or high step frequency (F X  > 155.13) achieve the best academic performance (AP = 78.0). It is the students who exhibit regular, slower-paced, and lower step frequency exercise patterns that excel in academic performance.

Impact of exercise performance indicators on academic performance from data model 2

When investigating the impact of exercise frequency and duration on academic performance, no significant differences were found in the decision tree analysis among all study subjects ( p  > 0.05). Therefore, the study sample was reduced, focusing primarily on students with good academic performance (AP > 80). From a total of 2,129 occurrences, 1,468 individuals (accounting for 68.9%) were selected as the new sample for further analysis, as depicted in Figure 3 .

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Figure 3 . CHAID decision tree analysis diagram based on data model 2.

Based on Figure 3 , it was evident that exercise frequency had a significant impact on achieving better academic performance ( p  < 0.00). As the number of exercise sessions (V X ) increased from 8 to 10, academic performance also increased from 80.01 to 82.46, exhibiting a linear correlation trend. Among the majority of students (65.6%), exercise frequency exceeded 10 sessions (V X  > 10). However, it was not the duration of each running session that determined the academic performance; instead, students (12.057%) with an average running time between 982.17 and 1555.33 s (16.4–26.1 min) achieved the best academic performance (AP = 83.632). Additionally, within this group of students, 44.69% had a running duration of less than 16 min, indicating relatively shorter running times and only meeting the minimum requirements. On the other hand, a small percentage (8.86%) of students had an average running time exceeding 26 min, indicating slower running speeds, primarily jogging or even walking, and insufficient intensity for cardiovascular exercise. Nodes 4 and Node 6 demonstrated a threshold effect, displaying an inverted U-shaped trend. While these students can also achieve satisfactory academic performance (AP > 82), their overall exercise effectiveness was inferior to that of students in Node 5, which exceeded the academic performance of approximately 88% of all other students.

The effect of activity tasks on academic performance

In our academic endeavor, we undertook a correlation validation analysis to address the first research question (Q1) and utilized the CHAID methodology to identify the most substantial influencing factors in addressing the second research question (Q2). In terms of academic performance, students who successfully complete assigned tasks may achieve satisfactory average grades. However, to attain higher academic performance (AP = 82.932), as depicted in Node 7 of Figure 2 , students not only need to demonstrate excellent activity regulation (H X  > 0.796) but also maintain a lower stride frequency (F X  < 155.13). This implies that students predominantly engage in jogging or walking, indicating lower exercise intensity compared to students in Node 8. It can be inferred that consistent engagement in low-intensity running promotes regular and sustained physical activity, indirectly affirming the endurance training component of exercise. This contributes to the development of students’ self-control and self-efficacy, which in turn aligns with their academic performance. In the academic domain, students are encouraged to cultivate a mindset of continuous learning and steadfastness, rather than relying solely on intense and short-term bursts of studying. It is through consistent effort and perseverance that students can build a solid foundation of knowledge and skills, enhancing their academic achievements in the long run. By integrating regular physical activity into their routines, students not only improve their cardiovascular and aerobic fitness but also develop important qualities such as discipline, focus, and resilience, all of which are conducive to academic success. This highlights the significance of maintaining a balanced approach to both physical exercise and academic pursuits, recognizing the synergistic relationship between the two domains. Therefore, emphasizing the value of consistent and moderate exercise contributes to the overall well-being and holistic development of students, ultimately benefiting their academic endeavors.

Optimal activity frequency and duration for academic performance

During the exploration of second research question (Q2), we sought to unravel the factors that exert a substantial influence on academic performance and simultaneously imbue interpretability into the realm of physical activity metrics, leveraging the capabilities of machine learning techniques. In pursuit of this objective, we turned to the CHAID method, a powerful tool that allowed us to identify and highlight the most pivotal influencing factors. According to Figure 2 , 67% of college students engage in physical activity with a frequency ranging from 7 to 14 times over the course of 12 weeks, which yields the maximum improvement in AP. Furthermore, 44.29% of students participate in physical activity between 10 and 14 times (at least once per week on average), resulting in favorable academic achievements (AP > 82). According to Figure 3 , students who engage in physical activity for durations ranging from 16 to 26 min demonstrate the highest predictive capability for academic performance. Although the proportion of these students in Node 5 is not high (12.06%), it reflects the positive impact of physical activity on improving cardiorespiratory endurance and regulating self-efficacy. Considering the average running distance, most students have covered over 2 kilometers after running for 16 min, which is a critical period for cardiorespiratory/aerobic fitness (C/AF) development. These students are capable of maintaining a moderate pace during running without rushing to complete the distance task. Their awareness of self-regulation efficiency influences goal selection, persistence in goal achievement, and response to setbacks, thereby enhancing their self-regulatory abilities ( Maddux et al., 2012 ). Allocating up to an additionally approximate half hour per day of curricular time to AP program does not affect the academic performance of primary school students negatively, even though the time allocated to other subjects usually shows a corresponding reduction.

Mechanism underlying the impact of physical activity on academic performance

To address research question (Q3), which pertains to elucidating the potential mechanisms by which establishing pathways may be beneficial, our study furnishes evidence for a mediating pathway within the impact mechanism. Specifically, we propose the pathway as follows: “physical exercise → self-control ability → academic performance.” The self-control ability is derived from college students engaging in low-intensity running during physical exercise, which allows them to control their speed without rushing to reach their fitness goals while still achieving the required intensity. It also supports the findings of Xu et al. (2018) , who concluded that executive function serves as an intermediate variable by which physical exercise promotes academic performance, explaining the pathway as “physical exercise → executive function → academic performance.” Furthermore, physical exercise offers the advantage of being regularly and consistently performed on a weekly basis, thus enhancing college students’ confidence and self-efficacy. This finding further corroborates with the research conclusion of Anderson et al. (2006) that while exercise directly influences academic performance, psychological-social factors and physical fitness levels play a mediating role. Through the expenditure of body fat calories during exercise, college students enhance their self-control ability and willpower, representing a self-regulatory structure that impacts individuals’ efforts to maintain consistency between cognition and behavior ( Anderson et al., 2006 ).

Data mining in sport education research

Physical activity involves complex decision-making processes, necessitating the utilization of effective tools and techniques to support physical educators. In the context of physical education research, it is essential to continuously explore the utilization of various research and experimental tools in practical investigations, fostering the in-depth application of advanced quantitative research methods and tools. In the domain of regression problems, it is imperative for machine learning algorithms to demonstrate not just robust predictive abilities, but also effective generalization. Therefore, in this study, the analysis extended beyond examining mean values of each indicator. To better capture the model’s generalization and explanatory power, the CHAID decision tree was employed, enabling statistical significance testing and offering comprehensive regression results ( Morgan et al., 2013 ). Decision trees, as a tool in machine learning have been playing a role in researching and solving complex problems in many fields, and has gained attention as a promising approach for tackling the intricacies and uncertainties associated with analyzing physical activity. Especially in the current era of big data, the abundance of data collected from observations of physical exercise (PE) and physical activity (PA) enables the emergence of behavioral patterns. By leveraging machine learning tools and statistical methods, the processing validity and reliability of physical observation data in complex systems can be improved ( Robertson and Joyce, 2015 ). This serves as the material foundation and underlying logic for educational data mining and data-driven approaches, which are essential for enhancing educational management and informed decision-making. For instance, unsupervised learning methods can be employed to classify or cluster groups based on sports-related data using entropy-based techniques ( Rhea et al., 2011 ; Namazi, 2021 ; Yang, 2021 ).

Limitations

First, this study leveraged a sizable sample for evaluating academic performance in relation to physical activity. Our research demonstrated an approach to enhance the interpretability and effectiveness of decision trees in processes. The challenges pertaining to missing physical exercise data, overfitting during model construction, and optimization of model parameters are to be addressed. Secondly, participants’ levels of physical activity may not be fully reflected in the data obtained from the running application (APP) since some special cases may have not been excluded completely, where low physical activity values could be due to student dropout or illness-related leaves and exceptionally high values could be attributed to student athletes or long-distance running enthusiasts ( Lupo et al., 2017a ). Thirdly, university students may engage in physical exercise for varying objectives, such as medals, participation in competitive events or improving their academic performance. Therefore, future research will delve further into the motivations behind physical exercise and their direct or indirect (mediating) impact on academic performance ( Lupo et al., 2017b ; Liang and Li, 2020 ).

This study utilized machine learning methods to investigate the impact of physical activity on academic achievement among undergraduates. The decision tree model effectively captured the relationship between physical and academic performance. Activity regularity exhibited varying degrees of influence on the interaction between physical test scores and academic achievement, and explaining the relationship between physical activity and academic achievement in terms of psycho-social factors and physical fitness level. These findings contribute to the existing literature on the subject and provide insights for educational practitioners to enhance academic performance through physical activity interventions.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were approved by Sichuan International Studies University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

SD: Formal analysis, Funding acquisition, Methodology, Writing – original draft, Writing – review & editing. HH: Supervision, Writing – review & editing. KC: Investigation, Validation, Writing – original draft, Writing – review & editing. HL: Methodology, Writing – review & editing.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by the Science and Technology Research Program of Chongqing Municipal Education Commission (Grant No. KJZD-K202200903).

Acknowledgments

Data were analyzed using college students at Sichuan International Studies University in China.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Anderson, D. F., Cychosz, C. M., and Franke, W. D. (1998). Association of exercise identity with measures of exercise commitment and physiological indicators of fitness in a law enforcement cohort. J. Sport Behav. 21, 233–241.

Google Scholar

Anderson, E. S., Wojcik, J. R., Winett, R. A., and Williams, D. M. (2006). Social-cognitive determinants of physical activity: the influence of social support, self-efficacy, outcome expectations, and self-regulation among participants in a church-based health promotion study. Health Psychol. 25, 510–520. doi: 10.1037/0278-6133.25.4.510

PubMed Abstract | CrossRef Full Text | Google Scholar

Balk, Y. A., and Englert, C. (2020). Recovery self-regulation in sport: theory, research, and practice. Int. J. Sports Sci. Coach. 15, 273–281. doi: 10.1177/1747954119897528

CrossRef Full Text | Google Scholar

Bandura, A. , (1997). Self-efficacy: the exercise of control . Freeman Press, New York, NY.

Bauman, A. E., Reis, R. S., Sallis, J. F., Wells, J. C., Loos, R. J. F., and Martin, B. W. (2012). Correlates of physical activity: why are some people physically active and others not? Lancet 380, 258–271. doi: 10.1016/S0140-6736(12)60735-1

Başkurt, Z., Başkurt, F., and Ercan, S. (2020). Correlations of physical fitness and academic achievement in undergraduate students. J. Phys. Educ. Hum. Move. 2, 9–20. doi: 10.24310/JPEHMjpehm.v2i1.6770

Bass, R. W., Brown, D. D., Laurson, K. R., and Coleman, M. M. (2013). Physical fitness and academic performance in middle school students[J]. Acta Paediatr. Scand. 102, 832–837. doi: 10.1111/apa.12278

Benediktus, N., and Oetama, R. S. (2020). The decision tree c5. 0 classification algorithm for predicting student academic performance. Ultimatics: Jurnal Teknik Informatika 12, 14–19. doi: 10.31937/ti.v12i1.1506

Chacón-Cuberos, R., Zurita-Ortega, F., Ramírez-Granizo, I., and Castro-Sánchez, M. (2020). Physical activity and academic performance in children and preadolescents: a systematic review. Apunts. Educación Física y Deportes 139, 1–9. doi: 10.5672/apunts.2014-0983.es.(2020/1).139.01

Chomitz, V. R., Slining, M. M., McGowan, R. J., Mitchell, S. E., Dawson, G. F., Hacker, K. A., et al. (2010). Is there a relationship between physical fitness and academic achievement? Positive results from public school children in the northeastern United States. J. Sch. Health 79, 30–37. doi: 10.1111/j.1746-1561.2008.00371.x

Colley, R.C., Garriguet, D., Janssen, I., Craig, C.L., Clarke, J., and Tremblay, M.S., (2011). Physical activity of Canadian adults: accelerometer results from the 2007 to 2009 Canadian health measures survey (no. 82-003-X). Retrieved from statistics Canada Canadian Centre for Health website. Available at: http://www.statcan.gc.ca/pub/82-003-x/2011001/article/11396-eng.htm

Eagle, S. R., Brent, D., Covassin, T., Elbin, R. J., Wallace, J., Ortega, J., et al. (2022). Exploration of race and ethnicity, sex, sport-related concussion, depression history, and suicide attempts in US youth. JAMA Netw. Open 5:e2219934. doi: 10.1001/jamanetworkopen.2022.19934

Esteban-Cornejo, I., Tejero-González, C. M., Martinez-Gomez, D., del-Campo, J., González-Galo, A., Padilla-Moledo, C., et al. (2014). Independent and combined influence of the components of physical fitness on academic performance in youth[J]. J. Pediatr. 165, 306–312.e2. doi: 10.1016/j.jpeds.2014.04.044

Farrahi, V., Niemelä, M., Kärmeniemi, M., Puhakka, S., Kangas, M., Korpelainen, R., et al. (2020). Correlates of physical activity behavior in adults: a data mining approach. Int. J. Behav. Nutr. Phys. Act. 17, 1–14. doi: 10.1186/s12966-020-00996-7

Gómez, M. Á., Battaglia, O., Lorenzo, A., Lorenzo, J., Jiménez, S., and Sampaio, J. (2015). Effectiveness during ball screens in elite basketball games. J. Sports Sci. 33, 1844–1852. doi: 10.1080/02640414.2015.1014829

Hijriana, N., and Muttaqin, R. (2016). Penerapan metode decision tree algoritma c4. 5 untuk klasifikasi mahasiswa berprestasi. Al-Ulum: J. Sains Teknol. 2, 39–43. doi: 10.31602/ajst.v2i1.651

Hussain, M., Zhu, W., Zhang, W., and Abidi, S. M. R. (2018). Student engagement predictions in an e-learning system and their impact on student course assessment scores. Comput. Intell. Neurosci. 2018:6347186. doi: 10.1155/2018/6347186

Ishihara, T., Morita, N., Nakajima, T., Okita, K., Sagawa, M., and Yamatsu, K. (2018). Modeling relationships of achievement motivation and physical fitness with academic performance in Japanese school children: moderation by gender[J]. Physiol. Behav. 194, 66–72. doi: 10.1016/j.physbeh.2018.04.031

Karthikeyan, V. G., Thangaraj, P., and Karthik, S. (2020). Towards developing hybrid educational data mining model (HEDM) for efficient and accurate student performance evaluation. Soft. Comput. 24, 18477–18487. doi: 10.1007/s00500-020-05075-4

Kayani, S., Kiyani, T., Wang, J., Zagalaz Sánchez, M., Kayani, S., and Qurban, H. (2018). Physical activity and academic performance: the mediating effect of self-esteem and depression[J]. Sustainability 10:3633. doi: 10.3390/su10103633

Koçak, Ö., Göksu, İ., and Göktas, Y. (2021). The factors affecting academic achievement: a systematic review of meta analyses. Int. Onl. J. Educ. Teach. 8, 454–484.

Liang, Z., and Li, M. L. (2020). Progress of research on physical health promotion and academic performance of adolescent children. J. Phys. Educ. 27, 96–102. doi: 10.16237/j.cnki.cn44-1404/g8.2020.03.015

Liang, D. C. (1994). Stress levels of college students and their relationship with physical activity. Chin. J. Ment. Health 1, 5–6. doi: 10.3321/j.issn:1000-6729.1994.01.020

Lupo, C., Mosso, C. O., Guidotti, F., Cugliari, G., Pizzigalli, L., and Rainoldi, A. (2017a). The adapted Italian version of the baller identity measurement scale to evaluate the student-athletes’ identity in relation to gender, age, type of sport, and competition level. PLoS One 12:e0169278. doi: 10.1371/journal.pone.0169278

Lupo, C., Mosso, C. O., Guidotti, F., Cugliari, G., Pizzigalli, L., and Rainoldi, A. (2017b). Motivation toward dual career of Italian student-athletes enrolled in different university paths. Sport Sci. Health 13, 485–494. doi: 10.1007/s11332-016-0327-4

Maddux, J. M. N., Schiffino, F. L., and Chang, S. E. (2012). The amygdala central nucleus: a new region implicated in habit learning. J. Neurosci. 32, 7769–7770. doi: 10.1523/JNEUROSCI.1223-12.2012

Mandorino, M., Figueiredo, A., Cima, G., and Tessitore, A. (2021). A data mining approach to predict non-contact injuries in young soccer players. Int. J. Comp. Sci. Sport 20, 147–163. doi: 10.2478/ijcss-2021-0009

Marques, A., Da, S., Hillman, C., and Sardinha, L. B. (2018). How does academic achievement relate to cardiorespiratory fitness, self-reported physical activity and objectively reported physical activity: a systematic review in children and adolescents aged 6-18 years. Br. J. Sports Med. 52:1039. doi: 10.1136/bjsports-2016-097361

Mooney, M., Charlton, P. C., Soltanzadeh, S., and Drew, M. K. (2017). Who ‘owns’ the injury or illness? Who ‘owns’ performance? Applying systems thinking to integrate health and performance in elite sport. Br. J. Sports Med. 51, 1054–1055. doi: 10.1136/bjsports-2016-096649

Morgan, S., Williams, M. D., and Barnes, C. (2013). Applying decision tree induction for identification of important attributes in one-versus-one player interactions: a hockey exemplar. J. Sports Sci. 31, 1031–1037. doi: 10.1080/02640414.2013.770906

Namazi, H. (2021). Complexity and information-based analysis of the heart rate variability (HRV) while sitting, hand biking, walking, and running. Fractals 29:2150201. doi: 10.1142/S0218348X21502017

Pei, D., Gong, Y., Kang, H., Zhang, C., and Guo, Q. (2019). Accurate and rapid screening model for potential diabetes mellitus. BMC Med. Inform. Decis. Mak. 19, 1–8. doi: 10.1186/s12911-019-0790-3

Rhea, C. K., Silver, T. A., Hong, S. L., Ryu, J. H., Studenka, B. E., Hughes, C. M., et al. (2011). Noise and complexity in human postural control: interpreting the different estimations of entropy. PLoS One 6:e17696. doi: 10.1371/journal.pone.0017696

Robertson, S. J., and Joyce, D. G. (2015). Informing in-season tactical eriodization in team sport: development of a match difficulty index for super Rugby. J. Sports Sci. 33, 99–107. doi: 10.1080/02640414.2014.925572

Robertson, S., Back, N., and Bartlett, J. D. (2016). Explaining match outcome in elite Australian rules football using team performance indicators. J. Sports Sci. 34, 637–644. doi: 10.1080/02640414.2015.1066026

Rodriguez, C. C., Camargo, E. M., Rodriguez-Añez, C. R., and Reis, R. S. (2020). Physical activity, physical fitness and academic achievement in adolescents: a systematic review. Rev. Bras. Med. Esporte 26, 441–448. doi: 10.1590/1517-8692202026052019_0048

Strachan, S. M., and Whaley, D. (2013). “Identities, schemas, and definitions: how aspects of the self influence exercise behaviour” in Handbook of physical activity and mental health . ed. P. Ekkekakis (New York: Routledge), 212–223.

Strachan, S. M., Brawley, L. R., and Spink, K. (2010). Glazebrook. Older adults’ physically-active identity: relationships between social cognitions, physical activity and satisfaction with life. Psychol. Sport Exerc. 11, 114–121. doi: 10.1016/j.psychsport.2009.09.002

Strachan, S. M., and Brawley, L. R. (2008). Reactions to a challenge to identity: a focus on exercise and healthy eating. J. Health Psychol. 13, 575–588. doi: 10.1177/1359105308090930

Sanz Arazuri, E., and de Leon Elizondo, A. P. (2010). Key to applying the CHAID algorithm: a study of university physical-sport leisure activities. Revista De Psicologia Del Deporte 19, 319–333.

Schnell, A., Mayer, J., Diehl, K., Zipfel, S., and Thiel, A. (2014). Giving everything for athletic success! – sports-specific risk acceptance of elite adolescent athletes. Psychol. Sport Exerc. 15, 165–172. doi: 10.1016/j.psychsport.2013.10.012

Shephard, R. J. (2015). Qualified fitness and exercise as professionals and exercise prescription: evolution of the PAR-Q and Canadian aerobic fitness test. J. Phys. Act. Health 12, 454–461. doi: 10.1123/jpah.2013-0473

Silva, P., Duarte, R., Esteves, P., Travassos, B., and Vilar, L. (2016). Application of entropy measures to analysis of performance in team sports. Int. J. Perform. Anal. Sport 16, 753–768. doi: 10.1080/24748668.2016.11868921

Thomas, S., Reading, J., and Shephard, R. J. (1992). Revision of the physical activity readiness questionnaire (PAR-Q). Can. J. Sport Sci. 17, 338–345.

PubMed Abstract | Google Scholar

Teixeira, J. E., Forte, P., Ferraz, R., Branquinho, L., Silva, A. J., Barbosa, T. M., et al. (2022). Methodological procedures for non-linear analyses of physiological and behavioural data in football. Exerc. Physiol. 1, 1–25. doi: 10.5772/intechopen.102577

Whitener, E. M. (1989). A meta-analytic review of the effect on learning of the interaction between prior achievement and instructional support. Rev. Educ. Res. 59, 65–86. doi: 10.3102/00346543059001065

Xu, W., Zhang, Y., Zhou, L., Hua, J., School, E., and University, Z. (2018). Influence of physical fitness on academic achievement in adolescents: evidences from a longitudinal study. Journal of Beijing Sports University 41, 70–76. doi: 10.19582/j.cnki.11-3785/g8.2018.07.010

Yang, B. (2021). Learning motivations and learning Behaviors of sports majors based on big data. Int. J. Emerg. Technol. Learn. 16, 86–97. doi: 10.3991/ijet.v16i23.27823

You, Y., Teng, W., Wang, J., Ma, G., Ma, A., Wang, J., et al. (2018). Hypertension and physical activity in middle-aged and older adults in China. Sci. Rep. 8:16098. doi: 10.1038/s41598-018-34617-y

Zhang, Y. (2022). An empirical study on the influence of college students’ physical fitness on the level of public health. J. Environ. Public Health 8:8197903. doi: 10.1155/2022/8197903

Keywords: complex systems, college students, physical activity, running, academic performance, decision tree

Citation: Du S, Hu H, Cheng K and Li H (2023) Exercise makes better mind: a data mining study on effect of physical activity on academic achievement of college students. Front. Psychol . 14:1271431. doi: 10.3389/fpsyg.2023.1271431

Received: 02 August 2023; Accepted: 27 September 2023; Published: 16 October 2023.

Reviewed by:

Copyright © 2023 Du, Hu, Cheng and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Huan Li, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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research paper in physical education

By Nancy Barile, Award-Winning Teacher, M.A.Ed.

While attending a three-day special education workshop, the book,  Spark: The Revolutionary New Science of Exercise and the Brain , was recommended to me on the basis that it provides incontrovertible evidence that exercise can help  all  students—especially special education students—improve in school. At a time when recess and physical education programs are being cut for test prep, I knew this was information worth having and sharing.

Exercise Can Improve Learning

Written by Dr. John J. Ratey, an associate clinical professor of psychiatry at Harvard Medical School, the book explores the connection between exercise and the brain, providing strong evidence that aerobic exercise physically remodels the brain for peak performance on all fronts. Specifically, Dr. Ratey writes that exercise improves learning on three levels: "First, it optimizes your mind-set to improve alertness, attention, and motivation; second, it prepares and encourages nerve cells to bind to one another, which is the cellular basis for logging in new information; and third, it spurs the development of new nerve cells from stem cells in the hippocampus." In short, not only does exercise help the brain get ready to learn but it actually makes retaining information easier.

A suburban school district outside of Chicago is proving this point. The Naperville, Illinois district implemented an early morning exercise program called Zero Hour, which sought to determine whether working out before school gives students a boost in their reading ability and other subjects. Since introducing this program, the district has seen remarkable results in both wellness and academic performance.

Naperville's philosophy was to teach kids how to monitor and maintain their own health and fitness—a lifestyle skill with enormous long-term benefits. In fact, across the country, research shows students with  higher fitness scores also have higher test scores . Physical activity has a "positive influence on memory, concentration, and classroom behavior."

Exercise Can Improve Students' Mental Health

Dr. Ratey's research also shows that exercise can be the best defense against a lot of the common mental health issues that students struggle with.

Our students face enormous stress in the classroom and in their lives, including peer pressure, work overload, and high stakes testing. Exercise controls the emotional and physical feelings of stress, and it also works at the cellular level. Physical activity is a natural way to prevent the negative consequences of stress because it can ward off the ill effects of chronic stress and actually reverse them. In addition, studies show people who add physical activity to their lives become more socially active, which boosts confidence and helps establish and maintain social connections.

Anxiety and Panic Disorders

Dr. Ratey defines anxiety as a natural reaction to a threat, but worrying when there's no real threat, to the point where one can't function normally, is an anxiety disorder. Panic is the most intense form of anxiety, and I've witnessed my students having panic attacks during tests and cooperative learning situations, or sometimes just from the general pressures of school.

Spark  points out that the majority of studies show aerobic exercise significantly reduces symptoms of anxiety disorders. Through exercise, people learn to alleviate anxiety and rebuild their confidence. Dr. Ratey points out that exercise reroutes the brain's circuits, reduces muscle tension, and teaches a different outcome to an anxiety-provoking situation, ultimately setting an anxious person free from their worrisome tendencies.

Aerobic exercise is known to have a positive impact on depressive symptoms.  Studies suggest  that endorphins produced in the brain during exercise contribute to a general feeling of well-being. Exercise also boosts dopamine, which improves mood and jump-starts the attention span. Thirty minutes of moderate exercise a few days a week can do wonders for students who suffer from depressive moods.

School can be an especially excruciating environment for students with attention deficit hyperactivity disorder (ADHD) because of the need to sit still, face forward, and listen. Dr. Ratey says structured exercise—in the form of martial arts, ballet, skateboarding, or gymnastics, for example—is one of the best treatment strategies for ADHD.

The combination of challenging both the brain and body is even better than just aerobic activity alone because the technicality of those sports activates brain areas that "control balance, timing, sequencing, evaluating consequences, switching, error correction, fine motor adjustment, inhibition, and, of course, intense focus and concentration."

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Published on 13.2.2024 in Vol 8 (2024)

The Effect of Web-Based Culinary Medicine to Enhance Protein Intake on Muscle Quality in Older Adults: Randomized Controlled Trial

Authors of this article:

Author Orcid Image

Original Paper

  • Emily Salas-Groves 1 , PhD   ; 
  • Michelle Alcorn 2 , PhD   ; 
  • Allison Childress 1 , PhD   ; 
  • Shannon Galyean 1 , PhD  

1 Nutritional Sciences, Texas Tech University, Lubbock, TX, United States

2 Hospitality and Retail Management, Texas Tech University, Lubbock, TX, United States

Corresponding Author:

Shannon Galyean, PhD

Nutritional Sciences

Texas Tech University

1301 Akron Avenue

Lubbock, TX, 79409

United States

Phone: 1 806 834 2286

Email: [email protected]

Background: The most common age-related musculoskeletal disorder is sarcopenia. Sarcopenia is the progressive and generalized loss of muscle mass, strength, and function. The causes of sarcopenia can include insufficient nutritional status, which may be due to protein-energy malnutrition, anorexia, limited food access and eating ability, or malabsorption. In the United States, 15.51% of older adults have been diagnosed with sarcopenia. Culinary medicine (CM) is a novel evidence-based medical field that combines the science of medicine with food and cooking to prevent and treat potential chronic diseases. CM helps individuals learn and practice culinary skills while tasting new recipes. Therefore, this program could successfully reduce barriers to protein intake, enabling older adults to enhance their diet and muscle quality.

Objective: This study aimed to examine how a web-based CM intervention, emphasizing convenient ways to increase lean red meat intake, could improve protein intake with the promotion of physical activity to see how this intervention could affect older adults’ muscle strength and mass.

Methods: A 16-week, single-center, parallel-group, randomized controlled trial was conducted to compare a web-based CM intervention group (CMG) with a control group (CG) while monitoring each group’s muscle strength, muscle mass, and physical activity for muscle quality. The CMG received weekly web-based cooking demonstrations and biweekly nutrition education videos about enhancing protein intake, whereas the CG just received the recipe handout. Anthropometrics, muscle mass, muscle strength, dietary habits, physical activity, and cooking effectiveness were established at baseline and measured after the intervention. The final number of participants for the data analysis was 24 in the CMG and 23 in the CG.

Results: No between-group difference in muscle mass ( P =.88) and strength (dominant P =.92 and nondominant P =.72) change from the prestudy visit was detected. No statistically significant difference in protein intake was seen between the groups ( P =.50). A nonsignificant time-by-intervention interaction was observed for daily protein intake ( P =.08). However, a statistically significant time effect was observed ( P ≤.001). Post hoc testing showed that daily protein intake was significantly higher at weeks 1 to 16 versus week 0 ( P <.05). At week 16, the intake was 16.9 (95% CI 5.77-27.97) g higher than that at the prestudy visit.

Conclusions: This study did not affect protein intake and muscle quality. Insufficient consistent protein intake, low physical activity, intervention adherence, and questionnaire accuracy could explain the results. These studies could include an interdisciplinary staff, different recruitment strategies, and different muscle mass measurements. Future research is needed to determine if this intervention is sustainable in the long term and should incorporate a follow-up to determine program efficacy on several long-term behavioral and health outcomes, including if the participants can sustain their heightened protein intake and how their cooking skills have changed.

Trial Registration: ClinicalTrials.gov NCT05593978; https://clinicaltrials.gov/ct2/show/NCT05593978

Introduction

The guidance of the National Institute on Aging classifies older adults as those aged 65 years and older [ 1 ]. As adults age, several age-related diseases can occur, the most common being cardiovascular disease, cancer, Alzheimer disease, Parkinson disease, osteoporosis, and sarcopenia [ 2 ]. A Global Burden of Disease study in 2017 [ 3 ] revealed that 31.4% of all diseases were age related. These age-related diseases, combined with the body and life changes that occur with aging, could contribute to compromised nutritional status. These body and life changes can be physiological, psychosocial, and economic [ 4 ]. All these factors play a significant role in nutrition and food choices, which are barriers to appetite and diet quality. Therefore, current research strategies aim to acquire healthy aging and prevent age-related diseases.

Aging can lead to age-related musculoskeletal disorders [ 5 ] caused by an imbalance between muscle protein’s anabolic and catabolic pathways, leading to overall skeletal muscle mass (SMM) loss [ 6 ]. The most common age-related musculoskeletal disorder is sarcopenia. Sarcopenia is the progressive and generalized loss of muscle mass, strength, and function [ 2 , 7 , 8 ]. Muscles affected include skeletal [ 9 ], smooth [ 10 ], and cardiac [ 11 ]. Consequently, sarcopenia increases fall and fracture risk [ 12 ], impairs daily living activities performance [ 13 ], increases cognitive impairment [ 14 ], decreases the quality of life [ 15 ], and leads to death [ 16 ].

In research, the general sarcopenia prevalence ranges from 0.2% to 86.5%, with prevalence in women ranging from 0.3% to 91.2% and prevalence in men ranging from 0.4% to 87.7% [ 17 ]. In the United States, 15.51% of older adults have been diagnosed with sarcopenia, demonstrating its magnitude of being a public health burden [ 18 ]. Therefore, early identification and intervention are the key factors for achieving improved sarcopenia outcomes. According to the European Working Group on Sarcopenia in Older People (EWGSOP), a sarcopenia diagnosis requires the measurements of muscle mass, strength, and function [ 6 ].

Although many factors lead to sarcopenia, the 2 crucial factors that can be controlled in older adults are inadequate nutritional intake and physical inactivity [ 19 , 20 ]. Older adults tend to have anabolic resistance, defined as “a blunted stimulation of muscle protein synthesis (MPS) to common anabolic stimuli in SMM” [ 21 ]. Therefore, increasing protein-dense food ingestion and habitual physical activity are frontline strategies to support muscle mass, performance, and health [ 21 ]. The Society for Sarcopenia, Cachexia, and Wasting Disease provided protein recommendations for treating and preventing sarcopenia at a minimum of 1.0 to 1.5 g/kg body weight per day with exercise [ 22 ]. The protein quality is also critical in age-related SMM anabolism. Research on how protein-rich whole foods (eg, lean red meat) can enhance MPS over supplementation in older adults is rising [ 23 ]. Recent data suggest that a moderate 113 g (30 g of protein) serving of animal protein (eg, lean beef) can increase MPS by approximately 50% [ 24 ]. Therefore, the per-meal anabolic threshold recommendation is 25 to 30 g of protein [ 23 - 25 ]. Unfortunately, older adults’ protein needs are usually not met. Independent older adults answered the 2005-2014 National Health and Nutrition Examination Survey (NHANES) [ 26 ], revealing that up to 46% are not meeting the protein intake recommendation.

Physical activity directly impacts muscle quality and quantity [ 27 ]. Inactivity in older adults can promote sarcopenia development [ 28 , 29 ], whereas physical activity increases muscle strength [ 30 , 31 ] and mass [ 32 , 33 ]. Therefore, physical activity is vital to lower sarcopenia prevalence [ 34 - 36 ]. Specifically, resistance training and balance exercises are considered the best for sarcopenia prevention [ 27 , 37 - 41 ]. Steps through activity trackers can help determine one’s physical activity [ 42 ]. Accomplishing 10,000 daily steps is suggested to positively influence body composition (eg, weight and body fat) and improve health parameters (eg, quality of life) [ 43 ]. Therefore, nutrition and physical activity have been seen to be essential in countering sarcopenia [ 44 ].

More interventions focusing on nutrition and lifestyle changes are essential in decreasing chronic disease and health care costs [ 45 ]. Educating and empowering individuals to change their lifestyles can be less costly than medications and invasive procedures [ 45 ]. Culinary medicine (CM) is a novel evidence-based medical field defined by combining the science of medicine with food and cooking [ 46 ]. CM differs from traditional lifestyle and nutrition interventions by attempting to empower the patient to care for herself or himself safely, effectively, and happily with food and beverages as a primary care technique [ 47 ]. It helps people access and eat nutrient-dense meals to prevent and treat potential chronic diseases [ 46 ]. Individuals learn and practice culinary skills while tasting new recipes [ 45 ]. Also, they can incorporate their favorite foods into their eating plan while learning how to enhance diet quality through new foods (eg, different types of vegetables) and meal preparation tips (eg, defrosting techniques) [ 47 , 48 ]. If executed appropriately, CM can be taught to all populations regardless of culinary skill, educational level, or socioeconomic background [ 45 ]. A CM curriculum typically includes practical applications in supermarkets and home kitchens [ 49 ]. These practical applications include basic nutrition knowledge and instruction on how to apply that knowledge to diet therapies [ 49 ]. However, limited studies report whether a web-based CM curriculum could be as effective as in-person.

Multiple randomized controlled trials report that CM significantly improved individuals’ culinary knowledge, healthy dietary patterns, and self‐efficacy for healthier cooking [ 50 - 54 ]. Thus, highlighting CM’s potential as a nutrition intervention could lower the risk of diet‐related chronic disease among older adults. However, few studies in this area include older adult participants; none exclusively focused on an older adult population, and only 6% of CM programs were taught by a qualified health professional [ 55 ]. Additionally, CM interventions have been very heterogeneous, indicating a lack of variety in how the intervention is conducted compared with others [ 55 ]. Therefore, this study could advance our knowledge of CM and sarcopenia prevention in older adults. A web-based CM program might be an innovative strategy to improve protein intake in independent older adults at home. In addition, this program could successfully reduce barriers to protein intake, enabling older adults to enhance their diet and muscle quality. This factor could be vital because research surrounding CM within older adults is in its infancy. Therefore, our study aimed to examine how a web-based CM intervention, emphasizing convenient ways to increase lean red meat intake, could improve protein intake with the promotion of physical activity to see how this intervention could affect older adults’ muscle strength and mass.

Study Design

A 16-week, single-center, parallel-group, randomized controlled trial compared a web-based CM intervention group (CMG) with a control group (CG) on their protein intake, cooking effectiveness, muscle strength, muscle mass, and physical activity. The study was conducted at Texas Tech University Nutrition and Metabolic Health Initiative (NMHI), Lubbock, Texas. Participants were permitted to remove themselves from the trial at any time.

Ethical Considerations

A human study compliance review was submitted to the institutional review board at Texas Tech University, Lubbock, Texas. The study was expedited for review and received approval (IRB2021-693). Once participants were recruited and eligibility was determined, an initial appointment was set up at Texas Tech University NMHI. A research team member described the study in detail, and participants were asked to sign a consent form stating willingness to participate. The participants’ information collected for the study was deidentified, given a code number, and kept on the researchers’ computer at Texas Tech University NMHI. The research team offered the participants the vívofit 4 watch (Garmin) as compensation, which they used to complete the study.

Recruitment, Screening, and Participants

Flyers, newsletters, and word of mouth were essential for recruitment. When participants agreed to enroll in the study, they filled out an initial screening questionnaire to help determine whether they met the eligibility criteria. The inclusion criteria involved individuals who are aged 65 years or older, able to cook for themselves, physically active (eg, no need for equipment for assistance), and able to use a computer and mobile device. The exclusion criteria included individuals aged <65 years; those with limited mobility (eg, need for equipment for assistance), cognitive dysfunction (eg, dementia), a heart pacemaker, or type 1 or type 2 diabetes with insulin use; current smokers; those with some form of amputation; those who unable to use a computer and mobile device or unable or unwilling to wear the vívofit 4 watch (Garmin) for the duration of the study; and those undergoing or had recently undergone a severe medical procedure or diagnosis.

Participants were recruited and enrolled from June 2022 to August 2022, with data collection completed in December 2022. If a participant dropped out of the study, a new participant would replace and be allotted to the same group as the participant they replaced. A total of 52 older adults, including both men and women, met the study’s eligibility criteria. Assessments were conducted at the prestudy, weekly, and poststudy time points.

Intervention Design and Study Procedures

Prestudy visit.

Before their visit, participants were told to refrain from exercising for 48 hours, taking alcohol for 12 hours, and wearing clothes with any metals. Informed consent was obtained before starting the assessments. The assessments included completing 4 questionnaires: Community Healthy Activities Model Program for Seniors (CHAMPS), Dietary Screener Questionnaire (DSQ), protein questionnaire, and cooking effectiveness questionnaire. Afterward, grip strength, height, and weight were measured. Then, the participants were scanned by dual-energy x-ray absorptiometry (DXA). After completing their scan, they were given a vívofit 4 watch (Garmin). Lastly, the participants were randomized to either CMG or CG and provided their study’s subject code (eg, Beef Study 01), grip strength and DXA results, and exercise handouts. Both groups were advised to consume 25 to 30 g of protein during every meal, and all questions were answered. A follow-up email was sent providing a sample of a 2-week workout plan based on the exercise recommendation handouts and reminders of the study protocol.

Weekly Interventions

The CMG received weekly web-based cooking demonstrations with a recipe handout and biweekly nutrition education video on general nutrition information based on the Nutrition Care Manual content from the Academy of Nutrition and Dietetics [ 56 ], all provided by email at the beginning of each week. Meanwhile, the CG just received the recipe handout by email. Therefore, this intervention was developed to show how effective the hands-on and visual intervention provided to the CMG is compared with just general reading of a recipe with no further education provided to the CG. In addition, at the end of each week, both groups received their weekly protein and cooking effectiveness questionnaires.

A total of 20 recipes focusing on lean ground beef were provided for this study. Before starting the study, the research team tested each recipe and adjusted it as needed based on visual, flavor, and dish size. Then, the cooking demonstration was recorded once the recipe was approved for the study. For weeks 1 and 2, three recipes were sent to the participants. For the remainder of the study, 1 recipe was sent weekly. In addition, educational videos on a specific nutrition topic were sent every 2 weeks. These topics provided the participants with further nutrition education, which is essential regarding their diet outside of protein.

Poststudy Visit

After their 16th week, the participants had their final data collected. At the end of the visit, the primary researcher shared the pre- and poststudy DXA and grip strength results with the participant and answered any questions.

Outcome Measurements

Questionnaires.

The following outcomes were measured: weekly activity level through CHAMPS, the diet through the DSQ, protein intake through a protein questionnaire, cooking confidence and attitude using a pre- and poststudy cooking effectiveness questionnaire, and intervention compliance through weekly cooking effectiveness.

CHAMPS is a 41-item questionnaire [ 57 ] that assesses the weekly frequency and duration of various lifestyle physical activities that are appropriate for older adults. The DSQ was developed for the 2009-2010 NHANES [ 58 ]. It is a 30-item questionnaire that assesses the frequency of consumption of selected foods and drinks in the past month, such as intakes of fruits and vegetables, red and processed meat, dairy or calcium products, added sugars, and whole grains or fiber. The protein questionnaire is a modified version of the rapid self-administered dietary protein food frequency questionnaire, which contains 37 items evaluating the weekly intake of different types of meat, dairy products, eggs, and beans [ 59 ].

Lastly, the pre- and poststudy cooking effectiveness questionnaires measured participants’ cooking confidence, attitudes, and challenges or barriers. In addition, the weekly cooking effectiveness reported each group’s compliance toward their intervention. The prestudy cooking effectiveness questionnaire includes 14 items, the weekly cooking effectiveness questionnaire includes 5 items, and the poststudy cooking effectiveness questionnaire includes 33 items.

Anthropometrics

Height was measured using a Charder HM: 200P stadiometer (Charder Electronic Co Ltd) to the nearest half inch. Body weight was measured by a Brecknell MS-1000 wheelchair scale (Brecknell) to the nearest 0.5 lbs.

Muscle Quality

Lean body and fat mass were measured using a Norland XR-800 DXA (Swissray International, Inc) to the nearest gram. Muscle strength was measured by a Camry Digital Hand Dynamometer (Camry Scale) to the nearest kilogram for dominant and nondominant hands. Steps were measured by the vívofit 4 watch (Garmin).

Statistical Analysis

The study was powered to identify pre- to poststudy changes between the groups. A similar study [ 60 ] was used to develop the necessary sample and effect size using the G*power software (version 3.1.9.6; Heinrich Heine University Düsseldorf). Calculations were made for a total sample of 52 participants (26 participants per group) to obtain a statistical difference in muscle strength and mass between the groups, assuming an α of 5%, effect size of 0.72, power of 80%, and 10% inflation for dropouts. Data were imported to SPSS (version 29; IBM Corp) for analysis. DXA measuring muscle and fat mass was the study’s primary outcome measure. Secondary outcomes included protein intake in grams, muscle strength in kilograms, average daily steps, frequency of physical activity in minutes per week, height in inches, and weight in kilograms.

Participants were randomized to the CMG or the CG by block randomization using 2 blocks with 26 codes. On the basis of the assigned participant’s study code, the primary researcher enrolled the participants into their group at the end of their initial visit. Therefore, the allocation was not concealed. The analysis assessed the effect of the intervention with the completers. Any missing data were replaced with the last observation carried forward before analyses of all measurements via single imputation. Participants were excluded from data analysis if they did not complete over 50% of their weekly questionnaires or, after enrollment, met an exclusion criterion.

Results are presented as mean (SD), mean (95% CI), ranges, or frequencies. P <.05 was considered statistically significant. Linear mixed models were used to assess the differences in protein intake between the groups at the end of the intervention. The model included the fixed effects of time, intervention, and time-by-intervention interaction. Participants were modeled as a random effect to account for the repeated measures design. When a significant main effect was observed, post hoc analyses were conducted and the Tukey-Kramer method was used to adjust for multiple comparisons. Within-group muscle mass and strength differences, as well as physical activity and diet quality differences, were estimated using an independent samples (1-tailed) t test for variables measured before and after the study.

Study Population

In total, 64 participants expressed interest in the study. Of these, 8 (13%) were excluded during web-based or telephone screening due to failing to meet the inclusion criteria or losing contact. A total of 56 participants were eligible for inclusion and were randomized: 29 to the CMG and 27 to the CG. A total of 25 participants in the CMG, compared with 24 in the CG, completed the 16-week weekly questionnaires and both study visits. Of the eligible 56 participants, 7 (13%) withdrew or dropped out before the completion of the study. Of the 7 participants, 6 (86%) dropped out due to medical reasons unrelated to the study, and 1 participant (14%) dropped out due to family reasons. Of the 56 participants, 2 (4%) participants had to be excluded from the data analysis because 1 participant had bariatric surgery during the study and the other completed less than 50% of their weekly questionnaires. Therefore, a total of 49 participants were included for the data analysis (CMG: 24/29, 83%; CG: 23/27, 85%). See the CONSORT (Consolidated Standards of Reporting Trials) study flow diagram ( Figure 1 ) for the study details.

research paper in physical education

The prestudy characteristics of the groups are presented in Table 1 . The study included a greater proportion of female (38/47, 81%) and White (44/47, 94%) participants. The mean age, weight, and BMI of the participants in the CMG were 71.4 (SD 5.2) years, 76.6 (SD 17.4) kg, and 28.0 (SD 6.0) kg/m 2 , respectively. In the CG, they were slightly older (mean 73.2, SD 5.8 years) but had lower weight (mean 69.4, SD 15.0 kg) and BMI (mean 26.1, SD 5.0 kg/m 2 ). The CG was found to be more physically active than the CMG. Regarding diet, the CG consumed more fiber, calcium, dairy, vegetables, and fruit than the CMG. Meanwhile, the CMG consumed more daily added sugar than the CG. However, both groups consumed the same amount of daily whole grains.

a Randomized controlled trial (June 2022 to August 2022; Texas Tech University Nutrition and Metabolic Health Initiative) evaluating the effect of a web-based culinary medicine intervention on protein intake, cooking effectiveness, muscle strength, muscle mass, and physical activity in an older adult population aged 65 years and older.

b CMG: culinary medicine intervention group.

c CG: control group.

d N/A: not applicable.

Muscle Mass and Strength Outcomes

There was no between-group difference in the muscle mass change from the prestudy visit ( P =.88; Table 2 ). Using the EWGSOP sarcopenia diagnosis [ 61 ], 21% (5/24) of the CMG and 26% (6/23) of the CG had low muscle mass at the prestudy visit. At the poststudy visit, 21% (5/24) of the CMG and 22% (5/23) of the CG had low muscle mass.

a The independent samples t test was used to compare between-group differences at the poststudy visit.

d P value refers to between-group differences by the independent samples t test.

e Not available.

Similar results were seen for muscle strength. There was no between-group difference in the muscle strength change from the prestudy visit (dominant: P =.92 and nondominant: P =.72). When comparing the classification of muscle strength for the dominant hand, the CMG was considered 29% (7/24) weak, 67% (16/24) normal, and 4% (1/24) strong at the prestudy visit. At the poststudy visit, the CMG was considered 33% (8/24) weak, 46% (11/24) normal, and 21% (5/24) strong. The CG was considered 13% (3/23) weak, 83% (19/23) normal, and 4% (1/23) strong at the prestudy visit. At the poststudy visit, the CG was considered 13% (3/23) weak, 74% (17/23) normal, and 13% (3/23) strong.

When comparing the classification of muscle strength for the nondominant hand, the CMG was considered 42% (10/24) weak, 54% (13/24) normal, and 4% (1/24) strong at the prestudy visit. At the poststudy visit, the CMG was considered 38% (9/24) weak, 50% (12/24) normal, and 13% (3/24) strong. On the other hand, the CG was considered 30% (7/23) weak, 65% (15/23) normal, and 4% (1/23) strong at the prestudy visit. At the poststudy visit, the CG was considered 30% (7/23) weak, 57% (13/23) normal, and 13% (3/23) strong.

Per the EWGSOP sarcopenia diagnosis [ 61 ], 38% (9/24) of the CMG and 30% (7/23) of the CG could be diagnosed with probable sarcopenia. In comparison, 8% (2/24) of the CMG and 9% (2/23) of the CG could be diagnosed with sarcopenia at the prestudy visit. At the poststudy visit, 33% (8/24) of the CMG and 17% (4/23) of the CG could be diagnosed with probable sarcopenia, whereas 8% (2/24) of the CMG and 9% (2/23) of the CG could be diagnosed with sarcopenia at the poststudy visit.

Protein Intake and Diet Quality

Figure 2 reveals the mean (SD) daily protein intake in grams for each week of the study for each group. A nonsignificant time-by-intervention interaction was observed for daily protein intake ( Figure 2 and Table 3 ; P =.08). There was also no statistically significant difference in protein intake between the interventions ( P =.50). However, a statistically significant time effect was observed ( P ≤.001). Post hoc testing showed that daily protein intake was significantly higher at weeks 1 to 16 versus week 0 ( P <.05) in the cohort. At week 16, protein intake was 16.9 (95% CI 5.77-27.97) g higher than that at the prestudy visit.

research paper in physical education

a Linear mixed-effects model analysis was used to compare between-group differences after the study for protein, whereas an independent samples t test was used for the remaining variables.

d P value refers to linear mixed-effects model analysis of between-group differences over time (time×treatment interaction).

Each group was evaluated to see how many participants met their protein needs (1.0-1.2 g/kg body mass per day). In the CG, 39% (9/23) participants did not meet their needs, 26% (6/23) did meet their needs, and 35% (8/23) exceeded their needs during the study. In the CMG, 58% (14/24) participants did not meet their needs, 8% (2/24) did meet their needs, and 33% (8/24) exceeded their needs during the study. Additionally, in all the completed protein questionnaires, the CMG and the CG had blank answers for 15.4% (63/408) and 12.5% (49/391) of their questions, respectively . When evaluating the daily intake for each dietary component from the DSQ ( Table 3 ), the components stayed close to the same when comparing pre- with poststudy results.

Cooking Effectiveness

For the CMG, participants reported watching 82.8% (318/384) of the intervention videos. The primary reason reported on why they did not watch the videos was “not interested in watching” (21/56, 38%). Additional reasons included personal reasons, traveling or vacation, or they did not receive the video. For the CG, participants reported that they read 94.8% (349/368) of the recipes sent to them. The primary reason why the participants did not read the recipe was “busy” (5/13, 39%). Additional reasons included personal and medical reasons, laziness, uninterest, not receiving the video, and having their spouse read it.

When examining whether both groups cooked the recipe learned through web-based videos or just by reading the recipe, the CMG cooked more recipes than the CG (64.8%, 249/384, vs 62.5%, 230/368). Based on the questionnaires with responses outside of “N/A,” the CMG and CG did not cook primarily because of “holiday, traveling, or vacation” (CMG: 20%, 25/125, and CG: 26.5%, 35/132). See Table 4 for the remaining reasons. Barriers or complications that were reported from both groups when either watching the videos or preparing the recipe included borrowing ingredients from a neighbor; recipe serving size being too big; confusion toward either the ingredients or methods; changing or not including ingredients to meet taste or diet preference; finding certain ingredients at the store; too much spice or ingredient in the recipe for their palette; standing for an extended period was challenging; difficulties in scheduling time and energy to shop, prepare, or cook; or taking more initiative to prepare recipe themselves.

a CMG: culinary medicine intervention group.

b CG: control group.

At the end of the study, both groups were asked about the main challenges or barriers to maintaining their protein intake ( Tables 5 and 6 ). Meanwhile, the CMG participants were asked how the CM videos specifically helped clarify managing their protein intake ( Table 7 ) and what the most memorable thing they recalled after watching the video or what their favorite part of the CM videos was. All CMG participants were reported having no technical difficulties accessing and watching the videos.

Principal Findings

To the authors’ knowledge, a study has yet to be performed with CM explicitly targeting the older adult population to enhance their protein intake. However, a statistically significant time effect was observed ( P ≤.001). Furthermore, post hoc testing showed that daily protein intake was significantly higher at weeks 1 to 16 versus week 0 ( P <.05). At week 16, protein intake was 16.9 (95% CI 5.77-27.97) g higher than that at the prestudy visit. This result indicates that protein intake increased in the cohort with the information provided to both groups.

Nevertheless, there was no additive effect of the CMG over what the CG received because no between-group differences were observed for any primary or secondary outcomes. Insufficient consistent protein intake, low physical activity, adherence to the intervention, and accuracy of the questionnaires could explain the results. Also, participants’ ethnicity, average age, gender, and BMI were similar in both groups and affected the diversity of the study’s population; therefore, the outcomes were not tested against them because there was no vast difference to indicate a relationship. Given the limited representation of men in the cohort, the results cannot be generalized to men, Hispanic participants, and African American participants.

The accuracy of each group’s protein questionnaire could play a factor because they were self-administered. Self-administered questionnaires are more susceptible to item nonresponse [ 62 ]. The CMG and the CG had blank answers for 15.4% (63/408) and 12.5% (49/391) of their questions, respectively, suggesting that their intake could have been higher and explained how their muscle mass was overall maintained. Additionally, the participants were not asked to change their diet outside their protein intake. The DSQ reported that participants’ diets did remain the same.

Comparison With Prior Work

Before the study started, both groups were recommended to consume 25 to 30 g of protein per meal in addition to daily physical activity. These recommendations are similar to Paddon-Jones and Rasmussen’s [ 63 ] findings, reporting that approximately 25 to 30 g of protein per meal is a valuable strategy for maintaining muscle mass in older adults. This strategy would mean that the participants would have to eat approximately 75 to 90 g of protein daily. The CMG met this range from weeks 6 to 15, but the CG met this range during weeks 4, 11, and 12. Specifically, 39% (9/23) of the CG and 58% (14/24) of the CMG did not meet their needs (1.0-1.2 g/kg body weight per day). The 2005-2014 NHANES [ 26 ] reported that 31% to 50% of older adults did not meet their protein recommendations. Our population was in this range. Therefore, these results could also explain why muscle mass did not significantly increase between the groups. However, the estimated average requirement for 51 to 70 years is 0.66 g/kg/d, and the recommended dietary intake is 0.8 g/kg/d for all adults over 18 years old, including older adults [ 64 ]. Therefore, in the context of adequate energy intake, muscle mass was maintained in this cohort if their protein intake was consistent with these levels.

Grip strength has been used in research to determine overall body strength [ 65 , 66 ]. However, there were no between-group differences in muscle strength change from the prestudy visit. Kim et al [ 67 ] found no association between the amount and change (increase or decrease) in daily total protein intake with the incidence or prevention of low muscle strength, which was similar to our results. Additionally, a longitudinal study [ 68 ] indicated that 25 to 30 g of protein per meal is associated with greater muscle strength in older adults. However, this recommended intake did not consistently happen in our study, and participants did not meet their calculated needs, which could affect their muscle strength. Physical activity also did not impact muscle strength. Similar results were seen with Ramsey et al [ 69 ], who also saw no association between the number of steps and handgrip strength.

When looking at their steps, current evidence suggests that healthy older adults should meet approximately 7000 to 10,000 steps per day [ 70 ]. However, our study showed that 67% (16/24) of the CMG and 57% (13/23) of the CG did not meet this range. Also, Park et al [ 34 ] reported that individuals who walked at least 7000 to 8000 steps daily likely have muscle mass above the sarcopenia threshold. Because only 33% of the CMG and 44% of the CG met this threshold, it is unsurprising that their lack of steps may have impacted our results.

Lastly, the dropout rates were similar, 14% (4/29) in the CMG and 11% (3/27) in the CG. This rate is lower than the reported average of 20% to 49%, which is commonly seen in dietary clinical trials [ 71 ]. In the CMG, 10% (3/29) of participants dropped out due to medical reasons, whereas 3% (1/29) dropped out due to family reasons. In the CG, all the participants dropped out due to medical reasons. These are all common reasons for dropouts in clinical trials [ 72 ]. The dropouts were not related to the study, and no adverse effects were reported throughout the study.

Strengths and Limitations

This study is the first to evaluate CM’s effect on enhancing protein intake and muscle quality in older adults, which brings a new aspect to existing CM research. Furthermore, this study allowed us to see if the intervention program improved their knowledge, awareness, and attitude toward protein intake within 4 months. In addition, the feedback from the participants can be applied to future studies.

A registered dietitian (RD), fully trained and qualified with years of experience, developed the whole program with assistance from those with expertise in food service and kinesiology. In addition, an RD implemented the intervention and provided advice if participants needed clarification about their intervention.

Our study had an overall dropout rate and data exclusion of 16% (9/56), limiting attrition bias. Additionally, there was a high response rate to the weekly questionnaires, with 84.6% (345/408) for the CMG versus 87.5% (342/391) for the CG, and the response rate goal for most research was approximately 60% [ 73 ]. This high response rate was credited to weekly adherence checks and effective accountability in recording their weekly questionnaires. Lastly, this intervention was low-cost and could be easily replicated and enhanced for future research.

Limitations

Although exercise recommendation handouts were given in this study, the main intervention has limitations with a focus on diet and nutrition education. A more comprehensive approach including digital CM education, exercise training sessions, and dietary supplementation would have allowed for a more adequate comparison and expectation of significant differences in muscle quality outcomes. Additionally, the result of this study may not be representative of the general population because the majority were female (38/47, 81%) and White (44/47, 94%), and their ages were similar. Therefore, this study would benefit from seeing its effect on those who lack cooking confidence and skills in addition to a more diverse population setting. In addition, there may be recall and social desirability biases as the questionnaires were self-reported, and the participants knew that the research team was reading the responses. This factor could be lessened through the interview-administered questionnaires. Finally, the protein questionnaire results may not be accurate because of the blank questions.

Some participants reported that they could not cook a recipe because they were on Weight Watchers or had self-proclaimed dietary restrictions (eg, no bread or pasta). This situation was seen in 15.2% (19/125) of the CMG and 2.3% (3/132) of the CG. Also, participants reported that some recipes could have been better for a different season (eg, chili in the winter instead of during the summer). They also voiced concern about some recipes needing smaller portions because they live alone. Additionally, because this intervention was performed in summer, fall, and the beginning of winter, the seasonal changes can explain why participants did not partake in some weeks of the study. For example, the participants did not cook their recipes because of holidays, traveling, or vacations (CMG: 20%, 25/125, and CG 26.5%, 35/132). Another example is that the colder weather and traveling could have impacted the results of the steps because most of the questions asked were about outdoor and in-house activities.

Conclusions and Future Direction

To the authors’ knowledge, this study is the first to examine the outcomes of CM in the form of web-based cooking demonstrations and nutrition education to enhance protein intake and muscle quality in older adults. The results reveal insufficient evidence because no between-group differences were observed for primary or secondary outcomes. However, most of the intervention group reported that the cooking demonstrations helped them prepare and cook recipes at home, providing more confidence in the kitchen, and its learning was feasible for them.

In the future, it would be valuable to further investigate the factors that could have affected this study. In developing and implementing this study, exercise training sessions and a dietary supplement could be included. Additionally, the research study design could include RDs, chefs, exercise physiologists, health coaches, or psychologists. The staff would be essential in creating the study protocol, kitchen equipment checklist, consent forms, scripts, and questions. During recruitment, it would be ideal to obtain a broad age range with an equal gender and ethnicity ratio to help reciprocate the general population. The recipes should consider the season, 1-person portion size, time, cost, and mild flavors. A protein food diary could help keep track of protein intake during the week and help answer the protein questionnaire accurately.

It could be interesting to incorporate muscle biopsy and biomarkers, such as vitamin B 12 , folate, and creatinine, to evaluate muscle mass further and see if this intervention impacts or could explain why muscle mass outcomes were nonsignificant due to predispositions. However, there are challenges in successfully performing a muscle biopsy in older men and women who are frail or have low body mass [ 74 ], so that would be a concern to consider. For biomarkers, no specific recommendations, references, or cutoff values are available to assess muscle mass or quality. Therefore, the biomarkers could be used to notice any significant change within a short time duration. Overall, given the current concern of sarcopenia, these concepts could enhance this intervention further with the information gathered in this study to impact public health.

Acknowledgments

The authors want to acknowledge Texas Tech University and Nutrition and Metabolic Health Initiative (NMHI) for the support of their facilities.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Conflicts of Interest

None declared.

CONSORT eHEALTH Checklist (V 1.6.2).

  • Age. National Institutes of Health. 2022. URL: https://www.nih.gov/nih-style-guide/age [accessed 2024-01-11]
  • Franceschi C, Garagnani P, Morsiani C, Conte M, Santoro A, Grignolio A, et al. The continuum of aging and age-related diseases: common mechanisms but different rates. Front Med (Lausanne). 2018;5:61. [ https://europepmc.org/abstract/MED/29662881 ] [ CrossRef ] [ Medline ]
  • GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789-1858. [ https://linkinghub.elsevier.com/retrieve/pii/S0140-6736(18)32279-7 ] [ CrossRef ] [ Medline ]
  • Malafarina V, Uriz-Otano F, Gil-Guerrero L, Iniesta R. The anorexia of ageing: physiopathology, prevalence, associated comorbidity and mortality. a systematic review. Maturitas. 2013;74(4):293-302. [ https://www.maturitas.org/article/S0378-5122(13)00025-X/fulltext ] [ CrossRef ] [ Medline ]
  • Li Z, Zhang Z, Ren Y, Wang Y, Fang J, Yue H, et al. Aging and age-related diseases: from mechanisms to therapeutic strategies. Biogerontology. 2021;22(2):165-187. [ https://europepmc.org/abstract/MED/33502634 ] [ CrossRef ] [ Medline ]
  • Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019;393(10191):2636-2646. [ CrossRef ] [ Medline ]
  • Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39(4):412-423. [ https://europepmc.org/abstract/MED/20392703 ] [ CrossRef ] [ Medline ]
  • de Souza Genaro P, Martini LA. Effect of protein intake on bone and muscle mass in the elderly. Nutr Rev. 2010;68(10):616-623. [ https://academic.oup.com/nutritionreviews/article/68/10/616/1811535?login=false ] [ CrossRef ] [ Medline ]
  • Lindle RS, Metter EJ, Lynch NA, Fleg JL, Fozard JL, Tobin J, et al. Age and gender comparisons of muscle strength in 654 women and men aged 20-93 yr. J Appl Physiol (1985). 1997;83(5):1581-1587. [ https://journals.physiology.org/doi/10.1152/jappl.1997.83.5.1581?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub 0pubmed ] [ CrossRef ] [ Medline ]
  • Kunieda T, Minamino T, Nishi JI, Tateno K, Oyama T, Katsuno T, et al. Angiotensin II induces premature senescence of vascular smooth muscle cells and accelerates the development of atherosclerosis via a p21-dependent pathway. Circulation. 2006;114(9):953-960. [ https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.106.626606 ] [ CrossRef ]
  • Lin J, Lopez EF, Jin Y, Van Remmen H, Bauch T, Han HC, et al. Age-related cardiac muscle sarcopenia: combining experimental and mathematical modeling to identify mechanisms. Exp Gerontol. 2008;43(4):296-306. [ https://europepmc.org/abstract/MED/18221848 ] [ CrossRef ] [ Medline ]
  • Schaap LA, van Schoor NM, Lips P, Visser M. Associations of sarcopenia definitions, and their components, with the incidence of recurrent falling and fractures: the longitudinal aging study Amsterdam. J Gerontol A Biol Sci Med Sci. 2018;73(9):1199-1204. [ https://academic.oup.com/biomedgerontology/article/73/9/1199/4782134?login=false ] [ CrossRef ] [ Medline ]
  • Malmstrom TK, Miller DK, Simonsick EM, Ferrucci L, Morley JE. SARC-F: a symptom score to predict persons with sarcopenia at risk for poor functional outcomes. J Cachexia Sarcopenia Muscle. 2016;7(1):28-36. [ https://europepmc.org/abstract/MED/27066316 ] [ CrossRef ] [ Medline ]
  • Chang KV, Hsu TH, Wu WT, Huang KC, Han DS. Association between sarcopenia and cognitive impairment: a systematic review and meta-analysis. J Am Med Dir Assoc. 2016;17(12):1164.e7-1164.e15. [ CrossRef ] [ Medline ]
  • Beaudart C, Biver E, Reginster JY, Rizzoli R, Rolland Y, Bautmans I, et al. Validation of the SarQoL, a specific health-related quality of life questionnaire for sarcopenia. J Cachexia Sarcopenia Muscle. 2017;8(2):238-244. [ https://europepmc.org/abstract/MED/27897430 ] [ CrossRef ] [ Medline ]
  • De Buyser SL, Petrovic M, Taes YE, Toye KRC, Kaufman JM, Lapauw B, et al. Validation of the FNIH sarcopenia criteria and SOF frailty index as predictors of long-term mortality in ambulatory older men. Age Ageing. 2016;45(5):602-608. [ https://academic.oup.com/ageing/article/45/5/602/2236632?login=false ] [ CrossRef ] [ Medline ]
  • Petermann-Rocha F, Balntzi V, Gray SR, Lara J, Ho FK, Pell JP, et al. Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta-analysis. J Cachexia Sarcopenia Muscle. 2022;13(1):86-99. [ https://europepmc.org/abstract/MED/34816624 ] [ CrossRef ] [ Medline ]
  • Du K, Goates S, Arensberg MB, Pereira S, Gaillard T. Prevalence of sarcopenia and sarcopenic obesity vary with race/ethnicity and advancing age. Divers Equal Health Care. 2018;15(4):175-183. [ https://diversityhealthcare.imedpub.com/prevalence-of-sarcopenia-and-sarcopenic-obesity-vary-with-raceethnicity-and-advancing-age.php?aid=23100 ] [ CrossRef ]
  • Naseeb MA, Volpe SL. Protein and exercise in the prevention of sarcopenia and aging. Nutr Res. 2017;40:1-20. [ CrossRef ] [ Medline ]
  • de Carvalho Bastone A, Nobre LN, de Souza Moreira B, Rosa IF, Ferreira GB, Santos DDL, et al. Independent and combined effect of home-based progressive resistance training and nutritional supplementation on muscle strength, muscle mass and physical function in dynapenic older adults with low protein intake: a randomized controlled trial. Arch Gerontol Geriatr. 2020;89:104098. [ CrossRef ] [ Medline ]
  • Paulussen KJM, McKenna CF, Beals JW, Wilund KR, Salvador AF, Burd NA. Anabolic resistance of muscle protein turnover comes in various shapes and sizes. Front Nutr. 2021;8:615849. [ https://europepmc.org/abstract/MED/34026802 ] [ CrossRef ] [ Medline ]
  • Morley JE, Argiles JM, Evans WJ, Bhasin S, Cella D, Deutz NEP, et al. Nutritional recommendations for the management of sarcopenia. J Am Med Dir Assoc. 2010;11(6):391-396. [ CrossRef ] [ Medline ]
  • Symons TB, Sheffield-Moore M, Wolfe RR, Paddon-Jones D. A moderate serving of high-quality protein maximally stimulates skeletal muscle protein synthesis in young and elderly subjects. J Am Diet Assoc. 2009;109(9):1582-1586. [ https://europepmc.org/abstract/MED/19699838 ] [ CrossRef ] [ Medline ]
  • Nowson C, O'Connell S. Protein requirements and recommendations for older people: a review. Nutrients. 2015;7(8):6874-6899. [ https://www.mdpi.com/resolver?pii=nu7085311 ] [ CrossRef ] [ Medline ]
  • Bauer J, Biolo G, Cederholm T, Cesari M, Cruz-Jentoft AJ, Morley JE, et al. Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group. J Am Med Dir Assoc. 2013;14(8):542-559. [ https://linkinghub.elsevier.com/retrieve/pii/S1525-8610(13)00326-5 ] [ CrossRef ] [ Medline ]
  • Krok-Schoen JL, Price AA, Luo M, Kelly OJ, Taylor CA. Low dietary protein intakes and associated dietary patterns and functional limitations in an aging population: a NHANES analysis. J Nutr Health Aging. 2019;23(4):338-347. [ https://europepmc.org/abstract/MED/30932132 ] [ CrossRef ] [ Medline ]
  • Breen L, Phillips SM. Interactions between exercise and nutrition to prevent muscle waste during ageing. Br J Clin Pharmacol. 2013;75(3):708-715. [ https://europepmc.org/abstract/MED/22957963 ] [ CrossRef ] [ Medline ]
  • Buford TW, Anton SD, Judge AR, Marzetti E, Wohlgemuth SE, Carter CS, et al. Models of accelerated sarcopenia: critical pieces for solving the puzzle of age-related muscle atrophy. Ageing Res Rev. 2010;9(4):369-383. [ https://europepmc.org/abstract/MED/20438881 ] [ CrossRef ] [ Medline ]
  • Evans WJ. Skeletal muscle loss: cachexia, sarcopenia, and inactivity. Am J Clin Nutr. 2010;91(4):1123S-1127S. [ https://linkinghub.elsevier.com/retrieve/pii/S0002-9165(23)01788-4 ] [ CrossRef ] [ Medline ]
  • Petrella JK, Kim JS, Tuggle SC, Bamman MM. Contributions of force and velocity to improved power with progressive resistance training in young and older adults. Eur J Appl Physiol. 2007;99(4):343-351. [ CrossRef ] [ Medline ]
  • Granacher U, Lacroix A, Muehlbauer T, Roettger K, Gollhofer A. Effects of core instability strength training on trunk muscle strength, spinal mobility, dynamic balance and functional mobility in older adults. Gerontology. 2013;59(2):105-113. [ CrossRef ] [ Medline ]
  • Candow D, Chilibeck PD, Abeysekara S, Zello GA. Short-term heavy resistance training eliminates age-related deficits in muscle mass and strength in healthy older males. J Strength Cond Res. 2011;25(2):326-333. [ https://journals.lww.com/nsca-jscr/fulltext/2011/02000/short_term_heavy_resistance_training_eliminates.6.aspx ] [ CrossRef ] [ Medline ]
  • Kosek DJ, Kim JS, Petrella JK, Cross JM, Bamman MM. Efficacy of 3 days/wk resistance training on myofiber hypertrophy and myogenic mechanisms in young vs. older adults. J Appl Physiol (1985). 2006;101(2):531-544. [ https://journals.physiology.org/doi/10.1152/japplphysiol.01474.2005?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub 0pubmed ] [ CrossRef ] [ Medline ]
  • Park H, Park S, Shephard RJ, Aoyagi Y. Yearlong physical activity and sarcopenia in older adults: the Nakanojo study. Eur J Appl Physiol. 2010;109(5):953-961. [ CrossRef ] [ Medline ]
  • Kim SH, Kim TH, Hwang HJ. The relationship of physical activity (PA) and walking with sarcopenia in Korean males aged 60 years and older using the Fourth Korean National Health and Nutrition Examination Survey (KNHANES IV-2, 3), 2008-2009. Arch Gerontol Geriatr. 2013;56(3):472-477. [ CrossRef ] [ Medline ]
  • Ryu M, Jo J, Lee Y, Chung YS, Kim KM, Baek WC. Association of physical activity with sarcopenia and sarcopenic obesity in community-dwelling older adults: the Fourth Korea National Health and Nutrition Examination Survey. Age Ageing. 2013;42(6):734-740. [ https://academic.oup.com/ageing/article/42/6/734/46751?login=false ] [ CrossRef ] [ Medline ]
  • Aagaard P, Suetta C, Caserotti P, Magnusson SP, Kjaer M. Role of the nervous system in sarcopenia and muscle atrophy with aging: strength training as a countermeasure. Scand J Med Sci Sports. 2010;20(1):49-64. [ https://onlinelibrary.wiley.com/doi/10.1111/j.1600-0838.2009.01084.x ] [ CrossRef ] [ Medline ]
  • Forbes SC, Little JP, Candow DG. Exercise and nutritional interventions for improving aging muscle health. Endocrine. 2012;42(1):29-38. [ CrossRef ] [ Medline ]
  • Hollmann W, Strüder HK, Tagarakis CVM, King G. Physical activity and the elderly. Eur J Cardiovasc Prev Rehabil. 2007;14(6):730-739. [ https://academic.oup.com/eurjpc/article/14/6/730/5933610?login=false ] [ CrossRef ] [ Medline ]
  • Kamel HK. Sarcopenia and aging. Nutr Rev. 2003;61(5):157-167. [ https://academic.oup.com/nutritionreviews/article/61/5/157/1839032?login=false ] [ CrossRef ] [ Medline ]
  • Mayer F, Scharhag-Rosenberger F, Carlsohn A, Cassel M, Müller S, Scharhag J. The intensity and effects of strength training in the elderly. Dtsch Arztebl Int. 2011;108(21):359-364. [ https://europepmc.org/abstract/MED/21691559 ] [ CrossRef ] [ Medline ]
  • Tedesco S, Sica M, Ancillao A, Timmons S, Barton J, O'Flynn B. Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults. PLoS One. 2019;14(5):e0216891. [ https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216891 ] [ CrossRef ] [ Medline ]
  • Le Hello C, Trombert B, Morel A, Chieh A, Brouard B, Boissier C. Performance analysis of walking of 10,000 regular users of a connected activity tracker. J Med Vasc. 2018;43(4):231-237. [ CrossRef ] [ Medline ]
  • Watanabe Y, Yamada Y, Yoshida T, Yokoyama K, Miyake M, Yamagata E, et al. Comprehensive geriatric intervention in community-dwelling older adults: a cluster-randomized controlled trial. J Cachexia Sarcopenia Muscle. 2020;11(1):26-37. [ https://europepmc.org/abstract/MED/31997543 ] [ CrossRef ] [ Medline ]
  • Mauriello LM, Artz K. Culinary medicine: bringing healthcare into the kitchen. Am J Health Promot. 2019;33(5):825-829. [ https://journals.sagepub.com/doi/10.1177/0890117119845711c ] [ CrossRef ] [ Medline ]
  • Puma JL. Culinary medicine and nature: foods that work together. Am J Lifestyle Med. 2020;14(2):143-146. [ https://europepmc.org/abstract/MED/32231479 ] [ CrossRef ] [ Medline ]
  • La Puma J. What is culinary medicine and what does it do? Popul Health Manag. 2016;19(1):1-3. [ https://europepmc.org/abstract/MED/26035069 ] [ CrossRef ] [ Medline ]
  • Freeland-Graves JH, Nitzke S, Academy of Nutrition and Dietetics. Position of the Academy of Nutrition and Dietetics: total diet approach to healthy eating. J Acad Nutr Diet. 2013;113(2):307-317. [ CrossRef ] [ Medline ]
  • Webb D. Culinary medicine. In: Today's Dietitian. Spring City, PA. Great Valley Publishing Company; 2023;16.
  • Monlezun DJ, Leong B, Joo E, Birkhead AG, Sarris L, Harlan TS. Novel longitudinal and propensity score matched analysis of hands-on cooking and nutrition education versus traditional clinical education among 627 medical students. Adv Prev Med. 2015;2015:656780-656788. [ https://doi.org/10.1155/2015/656780 ] [ CrossRef ] [ Medline ]
  • Birkhead AG, Foote S, Monlezun DJ, Loyd J, Joo E, Leong B, et al. Medical student-led community cooking classes: a novel preventive medicine model that's easy to swallow. Am J Prev Med. 2014;46(3):e41-e42. [ CrossRef ] [ Medline ]
  • Monlezun DJ, Dart L, Vanbeber A, Smith-Barbaro P, Costilla V, Samuel C, et al. Machine learning-augmented propensity score-adjusted multilevel mixed effects panel analysis of hands-on cooking and nutrition education versus traditional curriculum for medical students as preventive cardiology: multisite cohort study of 3,248 trainees over 5 years. Biomed Res Int. 2018;2018:5051289. [ https://doi.org/10.1155/2018/5051289 ] [ CrossRef ] [ Medline ]
  • Polak R, Dill D, Abrahamson MJ, Pojednic RM, Phillips EM. Innovation in diabetes care: improving consumption of healthy food through a "chef coaching" program: a case report. Glob Adv Health Med. 2014;3(6):42-48. [ https://europepmc.org/abstract/MED/25568831 ] [ CrossRef ] [ Medline ]
  • Ring M, Cheung E, Mahadevan R, Folkens S, Edens N. Cooking up health: a novel culinary medicine and service learning elective for health professional students. J Altern Complement Med. 2019;25(1):61-72. [ CrossRef ] [ Medline ]
  • Asher RC, Shrewsbury VA, Bucher T, Collins CE. Culinary medicine and culinary nutrition education for individuals with the capacity to influence health related behaviour change: a scoping review. J Hum Nutr Diet. 2022;35(2):388-395. [ CrossRef ] [ Medline ]
  • Nutrition Care Manual. 2023. URL: https://www.nutritioncaremanual.org/ [accessed 2024-01-11]
  • Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc. 2001;33(7):1126-1141. [ https://journals.lww.com/acsm-msse/fulltext/2001/07000/champs_physical_activity_questionnaire_for_older.10.aspx ] [ CrossRef ] [ Medline ]
  • Thompson FE, Midthune D, Kahle L, Dodd KW. Development and evaluation of the National Cancer Institute's dietary screener questionnaire scoring algorithms. J Nutr. 2017;147(6):1226-1233. [ https://linkinghub.elsevier.com/retrieve/pii/S0022-3166(22)10777-7 ] [ CrossRef ] [ Medline ]
  • Morin P, Herrmann F, Ammann P, Uebelhart B, Rizzoli R. A rapid self-administered food frequency questionnaire for the evaluation of dietary protein intake. Clin Nutr. 2005;24(5):768-774. [ CrossRef ] [ Medline ]
  • Alemán-Mateo H, Carreón VR, Macías L, Astiazaran-García H, Gallegos-Aguilar AC, Enríquez JRR. Nutrient-rich dairy proteins improve appendicular skeletal muscle mass and physical performance, and attenuate the loss of muscle strength in older men and women subjects: a single-blind randomized clinical trial. Clin Interv Aging. 2014;9:1517-1525. [ https://europepmc.org/abstract/MED/25258523 ] [ CrossRef ] [ Medline ]
  • Giovannini S, Brau F, Forino R, Berti A, D'Ignazio F, Loreti C, et al. Sarcopenia: diagnosis and management, state of the art and contribution of ultrasound. J Clin Med. 2021;10(23):5552. [ https://www.mdpi.com/resolver?pii=jcm10235552 ] [ CrossRef ] [ Medline ]
  • Edwards P. Questionnaires in clinical trials: guidelines for optimal design and administration. Trials. 2010;11:2. [ https://trialsjournal.biomedcentral.com/articles/10.1186/1745-6215-11-2 ] [ CrossRef ] [ Medline ]
  • Paddon-Jones D, Rasmussen BB. Dietary protein recommendations and the prevention of sarcopenia. Curr Opin Clin Nutr Metab Care. 2009;12(1):86-90. [ https://europepmc.org/abstract/MED/19057193 ] [ CrossRef ] [ Medline ]
  • Baum JI, Kim IY, Wolfe RR. Protein consumption and the elderly: what is the optimal level of intake? Nutrients. 2016;8(6):359. [ https://www.mdpi.com/resolver?pii=nu8060359 ] [ CrossRef ] [ Medline ]
  • Kozakai R. Grip strength and healthy aging. J Phys Fitness Sports Med. 2017;6(3):145-149. [ https://www.jstage.jst.go.jp/article/jpfsm/6/3/6_145/_article ] [ CrossRef ]
  • Cesari M, Fielding RA, Pahor M, Goodpaster B, Hellerstein M, van Kan GA, et al. Biomarkers of sarcopenia in clinical trials-recommendations from the International Working Group on Sarcopenia. J Cachexia Sarcopenia Muscle. 2012;3(3):181-190. [ https://air.unimi.it/handle/2434/550825 ] [ CrossRef ] [ Medline ]
  • Kim HN, Kim SH, Eun YM, Song SW. Impact of dietary protein intake on the incidence of low muscle strength in middle-aged and older adults. Clin Nutr. 2021;40(4):1467-1474. [ CrossRef ] [ Medline ]
  • Farsijani S, Payette H, Morais JA, Shatenstein B, Gaudreau P, Chevalier S. Even mealtime distribution of protein intake is associated with greater muscle strength, but not with 3-y physical function decline, in free-living older adults: the Quebec longitudinal study on nutrition as a determinant of successful aging (NuAge study). Am J Clin Nutr. 2017;106(1):113-124. [ https://linkinghub.elsevier.com/retrieve/pii/S0002-9165(22)02512-6 ] [ CrossRef ] [ Medline ]
  • Ramsey KA, Meskers CGM, Maier AB. Every step counts: synthesising reviews associating objectively measured physical activity and sedentary behaviour with clinical outcomes in community-dwelling older adults. Lancet Healthy Longev. 2021;2(11):e764-e772. [ https://linkinghub.elsevier.com/retrieve/pii/S2666-7568(21)00203-8 ] [ CrossRef ] [ Medline ]
  • Tudor-Locke C, Craig CL, Aoyagi Y, Bell RC, Croteau KA, De Bourdeaudhuij I, et al. How many steps/day are enough? For older adults and special populations. Int J Behav Nutr Phys Act. 2011;8:80. [ https://ijbnpa.biomedcentral.com/articles/10.1186/1479-5868-8-80 ] [ CrossRef ] [ Medline ]
  • Mirmiran P, Bahadoran Z, Gaeini Z. Common limitations and challenges of dietary clinical trials for translation into clinical practices. Int J Endocrinol Metab. 2021;19(3):e108170. [ https://europepmc.org/abstract/MED/34567133 ] [ CrossRef ] [ Medline ]
  • DeSouza CM, Legedza ATR, Sankoh AJ. An overview of practical approaches for handling missing data in clinical trials. J Biopharm Stat. 2009;19(6):1055-1073. [ CrossRef ] [ Medline ]
  • Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. Am J Pharm Educ. 2008;72(2):43. [ https://europepmc.org/abstract/MED/18483608 ] [ CrossRef ] [ Medline ]
  • Wilson D, Breen L, Lord JM, Sapey E. The challenges of muscle biopsy in a community based geriatric population. BMC Res Notes. 2018;11(1):830. [ https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-018-3947-8 ] [ CrossRef ] [ Medline ]

Abbreviations

Edited by A Mavragani; submitted 24.05.23; peer-reviewed by P Shankar, MN Shalaby; comments to author 05.12.23; revised version received 19.12.23; accepted 21.12.23; published 13.02.24

©Emily Salas-Groves, Michelle Alcorn, Allison Childress, Shannon Galyean. Originally published in JMIR Formative Research (https://formative.jmir.org), 13.02.2024.

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  • MyU : For Students, Faculty, and Staff

College of Science and Engineering

Two University of Minnesota professors elected to the National Academy of Engineering in 2024

Six alumni also elected to receive the highest professional honor awarded to an engineer.

MINNEAPOLIS / ST. PAUL (02/07/2024)—University of Minnesota-Twin Cities College of Science and Engineering Professors Catherine French and Timothy Lodge have been elected to the National Academy of Engineering (NAE). This is among the highest professional distinctions awarded to an engineer. The NAE elected only 114 new members and 21 foreign members this year. Six University of Minnesota alumni were also elected to NAE this year..

Professor Catherine E. French

Catherine E. French , a College of Science and Engineering Distinguished Professor in the Department of Civil, Environmental, and Geo- Engineering, is a renowned structural engineer. She was recognized by NAE for “design, safety, and construction of structural concrete buildings and bridges.” Her research interests include the behavior of reinforced and prestressed concrete structural systems, field monitoring of structures, numerical and experimental investigations of structural systems including time-dependent and environmental effects, evaluation and repair of damaged structures, and development and application of new materials. She has served on the national concrete building code committee for nearly 30 years.

A professor at the University of Minnesota since 1984, French has received numerous awards for her research and teaching from the University and professional organizations. Among those is being named an American Society of Civil Engineers (ASCE) Distinguished Member and an American Concrete Institute Honorary Member. Since 2019, she has been a member of the University of Minnesota Academy of Distinguished Teachers.

She has mentored more than 85 graduate students, postdoctoral researchers, and visiting scholars. She also has published and edited more than 175 research papers, publications and discussions.

French earned a bachelor’s degree in civil engineering from the University of Minnesota Twin Cities and master’s and Ph.D. degrees in civil engineering from the University of Illinois at Urbana-Champaign.

Professor Timothy P. Lodge

Timothy P. Lodge is a University of Minnesota Regents Professor in the Department of Chemistry and in the Department of Chemical Engineering and Materials Science.. He is a renowned polymer scientist. Potential applications of his work include improved delivery of medicines within the body, viscosity modification of lubricating oils, and nanostructure templating. Lodge is honored by NAE for “contributions to the understanding of the dynamic properties of multicomponent polymers and self-assembled structures.”

A professor at the University of Minnesota since 1982, Lodge currently holds the Prager Chair in Macromolecular Science in Chemistry and is a College of Science and Engineering Distinguished Professor. From 2005-2022 he served as Director of the University of Minnesota Materials Research Science and Engineering Center (MRSEC), funded by the National Science Foundation. 

Lodge has received numerous awards including being named a Fellow of the American Academy of Arts and Sciences and the Paul Flory Education Award from the American Chemical Society (ACS). He was Editor-in-Chief of the ACS journal Macromolecules from 2001–2017, and  was the founding editor of ACS Macro Letters.

A sought-after teacher and adviser, Lodge has trained more than 100 graduate students, 100 undergraduates, and 50 postdoctoral associates. He has also published more than 500 research papers.

Lodge earned his bachelor's degree in applied mathematics from Harvard, and his doctorate in chemistry from the University of Wisconsin-Madison.

University of Minnesota College of Science and Engineering Alumni

Six University of Minnesota alumni were also elected to the NAE in 2024. They are:

Martha C. Anderson , research physical scientist, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Md., for application of thermal satellite remote sensing in hydrology. Anderson received her Ph.D. in astrophysics from the University of Minnesota in 1993.

Patrick R. Gruber , chief executive officer and director, Gevo Inc., Englewood, Colo., for renewable resource-based chemicals, plastics, and fuels, demonstrated by scalable, economically viable processes. Gruber received his Ph.D. in chemistry from the University of Minnesota in 1989.

Kei May Lau , chair professor in microelectronics thrust, School of Engineering, The Hong Kong University of Science and Technology, Kowloon, for photonics and electronics based on III-V semiconductors on silicon. Lau received her bachelor’s and master’s degrees in physics from the University of Minnesota in 1976 and 1977 respectively. 

Jeffery J. Puschell , engineer, Northrop Grumman Corp., El Segundo, Calif., for development of optical, multispectral, and hyperspectral space-based remote sensing systems for Earth observation. Puschell received his Ph.D. in physics from the University of Minnesota in 1979.

Dawn M. Tilbury , Ronald D. and Regina C. McNeil Department Chair of Robotics and professor of robotics, University of Michigan, Ann Arbor, for advances in manufacturing network control and human-robot interaction and for engineering leadership. Tilbury received her bachelor’s degree in electrical engineering from the University of Minnesota in 1989.

International members

Stephane Bancel , chief executive officer, Moderna Inc., Cambridge, Mass., for development and manufacturing of pharmaceutical products, including the COVID-19 vaccine. Bancel received his master’s degree in chemical engineering from the University of Minnesota in 1995.

Individuals in the newly elected class will be formally inducted during the NAE's annual meeting on Sept. 29, 2024. More information on today’s elections, including a list of the newly elected members and foreign associates, is available on the  National Academy of Engineering website .

Catherine French and Timothy Lodge combo portrait for National Academy of Engineering

Rhonda Zurn, College of Science and Engineering,  [email protected]

University Public Relations,  [email protected]

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COMMENTS

  1. Physical Activity, Fitness, and Physical Education: Effects on Academic Performance

    Pontifex et al., 2011) have examined the P3 component of the stimulus-locked ERP and demonstrated that higher-fit children have larger-amplitude and shorter-latency ERPs relative to their lower-fit peers.

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    1.0 Summary 4 2.0 Introduction 6 3.0 The impact of physical education, physical activity and sport on academic achievement 8 4.0 The impact of PE, physical activity and sport on cognitive function. 14 5.0 The impact of physical education, physical activity and sport on classroom behaviours that may impact on academic achievement. 20

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  15. The Impact of Physical Education on Students' Performance Outcomes in

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  16. PDF Increasing Student Physical Fitness Through Increased Choice of Fitness

    research were physical education students in grades 10 - 12. The students exhibited physical fitness levels below that of the state and national norms, and also displayed negative attitudes about physical fitness. Evidence for the existence of the problem included data collected from a

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    In this guide on physical education research paper topics, we explore a wide range of subjects that delve into the field of physical education. Whether you're a student studying education or a researcher in the field, this comprehensive list of topics is designed to inspire and guide you in your research endeavors.

  18. Exercise makes better mind: a data mining study on effect of physical

    In this paper, we collected the data on both physical activity and academic performance from 2,219 undergraduate students (Mean = 19 years) over a continuous period of 12 weeks within one academic semester. ... Data mining in sport education research. Physical activity involves complex decision-making processes, necessitating the utilization of ...

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  23. Sequential Treatment by Ozonation and Biodegradation of Pulp and Paper

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  24. JMIR Formative Research

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  25. Two University of Minnesota professors elected to the National Academy

    Six alumni also elected to receive the highest professional honor awarded to an engineerMINNEAPOLIS / ST. PAUL (02/07/2024)—University of Minnesota-Twin Cities College of Science and Engineering Professors Catherine French and Timothy Lodge have been elected to the National Academy of Engineering (NAE). This is among the highest professional distinctions awarded to an engineer.