Effects of Physical Exercise Intervention on Motor Skills and Executive Functions in Children With ADHD: A Pilot Study

Abstract

Objective: This study examined the effect of a 12-week table tennis exercise on motor skills and executive functions in children with ADHD. Method: Fifteen children with ADHD received the intervention, whereas 15 children with ADHD and 30 typically developing children did not. The Test of Gross Motor Development–2, Stroop, and Wisconsin Card Sorting Test (WCST) were conducted before and after the intervention. Results: After the intervention, the ADHD training group scored significantly higher in the locomotor as well as object-control skills, Stroop Color–Word condition, and WCST total correct performance compared with the ADHD non-training group, and we noted improvements in the locomotor as well as object-control skills, Stroop Color–Word condition, and three aspects of the WCST performances of the ADHD training group over time. Conclusion: A 12-week table tennis exercise may have clinical relevance in motor skills and executive functions of children with ADHD.

Keywords

ADHD physical exercise motor skills executive functions

Introduction

ADHD is a neurodevelopmental disorder identified through developmentally inappropriate symptoms of inattention, impulsiveness, and overactivity, which must occur for at least 6 months in at least two domains of life and begin to be observed before the age of 7 years (American Psychiatric Association [APA], 2013). These symptoms typically emerge in early childhood, commonly persist through adolescence and into adulthood, and can cause numerous impairments in social, academic, and occupational functioning, in addition to high rates of substance abuse (Mannuzza & Klein, 2000). Furthermore, several studies have documented motor skill deficits in ADHD, including those related to gross (Harvey et al., 2009; Pan, Tsai, & Chu, 2009; Scharoun, Bryden, Otipkova, Musalek, & Lejcarova, 2013) and fine motor skills (Liavasani & Stagnitti, 2013; Scharoun et al., 2013). Poor motor skill performance can place children with ADHD at risk of developing a weak self-concept, high anxiety levels, and a poor social function (Ayaz, Ayaz, Yazgan, & Akın, 2013; Skinner & Piek, 2001), in addition to contributing to physical inactivity and a lack of fitness. Pan et al. (2017) indicated that children with ADHD exhibited poorer motor skill performance and cardiovascular function compared with typically developing (TD) children, at baseline. In addition, poor motor skill performance has been linked to childhood obesity in TD children (Morano, Colella, Robazza, Bortoli, & Capranica, 2011). Yang, Mao, Zhang, Li, and Zhao (2013) indicated that the prevalence of obesity in children with ADHD is higher compared with the general population. These social and behavioral deficits associated with ADHD as well as motor skill impairments could thus clearly affect a child’s ability to reach his or her potential.

Conventional treatments for ADHD include medication and behavioral modification, which have both been proven scientifically to be effective. Although these standard ADHD treatments are widely accepted as the most compelling evidence-based interventions, not all children respond well to these pharmacological or behavioral interventions, despite intensive treatments (Hoza et al., 2005), and effects are rarely maintained beyond active intervention (Halperin & Healey, 2011). In addition, certain parents are unwilling to medicate their children because they are often concerned with their safety, notable side effects, and medication-related risks. Likewise, numerous families are unable to access counseling for behavioral modification, and behavioral interventions with high levels of fidelity over long periods are difficult to implement and are typically relatively expensive and challenging. Hence, no apparent changes exist in the underlying deficits that produce the behavioral manifestations of ADHD. Because of the lack of a clear improvement in long-term functioning as well as difficulties in long-term adherence to both medication and behavioral interventions, there is a need for novel, alternative strategies that families, schools, and individuals can use to manage the disorder over a long period of time.

The idea that physical exercise could be utilized to manage the broad spectrum of symptoms and impairments (e.g., motor skills, neuropsychological parameters) that characterize ADHD is both innovative and exciting (Kamp, Sperlich, & Holmberg, 2014; Wigal, Emmerson, Gehricke, & Galassetti, 2013). The exact mechanism by which physical exercise might ameliorate symptoms and cognitive functions of ADHD has not been conclusively determined. Prominent hypothesis indicated that physical exercise naturally stimulates adrenoneurogenic mediators that are similar to the pharmacological agents commonly used in ADHD therapy (Wigal et al., 2013). Specifically, physical exercise may benefit behavioral and cognitive outcomes through increased levels of neurotransmitter (e.g., dopamine, serotonin, norepinephrine) and neurotrophins (e.g., brain-derived neurotrophic factor). Regardless of the specific mechanism, physical exercise appears to foster brain health in ways that could complement current therapeutic approaches in the treatment of ADHD.

The limited existing studies of acute (Chang, Liu, Yu, & Lee, 2012) or chronic (Chang, Hung, Huang, Hatfield, & Hung, 2014; Smith et al., 2013; Verret, Guay, Berthiaume, Gardiner, & Beliveau, 2012) physical exercise on cognitive performance or behavioral functioning of youths diagnosed with, or at risk for, ADHD suggest positive effects. Chang et al. (2012) examined the impact of acute aerobic exercise on executive functions in children diagnosed with ADHD. Their participants performed moderate-intensity exercise on a treadmill for 30 min, and their executive functions were tested before and immediately after a single session of the exercise by using the Stroop Color–Word Test and the Wisconsin Card Sorting Test (WCST). Children in the exercise group demonstrated specific significant improvements in performance compared with the controls (i.e., viewing exercise videos) on the Stroop Color–Word condition (i.e., the selective attention or inhibition of a dominant response), WCST non-perseverative errors (i.e., efficiency of incorrect set shifting), and categories completed (i.e., correct set shifting). However, no exercise effects between groups were found in the other indices from the WCST, suggesting that acute exercise sensitivity was limited for these aspects. Verret et al. (2012) used a between-subjects experimental design to assess the effects of a 10-week (45 min, three times a week) moderate- to high-intensity physical activity program in a school gymnasium on fitness, cognitive function, and behavior in a sample of 21 elementary school-aged children with ADHD. Their results indicated that the children who performed exercise experienced significant gains in muscular capacity (i.e., pushups), motor performance (i.e., locomotion and total gross motor skills), behavior (i.e., social, thought, and attention problems) reported by parents, and neuropsychological measures (i.e., the levels of information processing and auditory sustained attention). Chang et al. (2014) conducted a between-subjects experimental study to investigate the impact of an 8-week (90 min, twice per week) aquatic exercise intervention that involved both aerobic and coordinative exercises on inhibitory control in 15 children with ADHD relative to a wait-list control group of 15 children with ADHD. The children were assessed using the Go/No-Go task and motor ability before and after the 8-week exercise or control intervention. Children in the exercise group demonstrated significant improvements in accuracy for the No-Go stimulus after the intervention, and motor skill coordination was observed over time relative to the controls. Smith et al. (2013) employed a within-subjects experimental design to examine the effects of an 8-week before-school physical activity intervention (30 min, five times a week) on 17 children (Grades K-3) exhibiting at least four hyperactivity or impulsivity symptoms. These children completed approximately 26 min of continuous moderate-to-vigorous physical activity (MVPA) daily, with good program attendance. The findings revealed significant improvements in the pre–post program measures of gross and fine motor proficiency and response inhibition, in addition to the weekly measures of response inhibition and problem behaviors (i.e., inattention and overactivity, oppositional and defiant behavior). Overall, these four pilot studies provided preliminary evidence on the potential of exercise interventions in improving both the behavioral and neuropsychological functions of school-aged children with ADHD.

However, these studies have focused primarily on aerobic exercise or quantitative exercise characteristics (i.e., intensity, duration, and frequency). Pesce (2012) claimed that we must explore whether and how the qualitative aspects of physical exercise (e.g., open skill exercise or a combination of complex skills) may affect physical and cognitive performance in the short and long term. Therefore, for the present study, we developed a 12-week (2 days per week, 70 min per day) physical exercise that involved training in motor skills and perhaps executive functions through a table tennis program. There are several benefits to using a table tennis program, merging both physical and cognitive training, with this young population. First, a successful performance in a table tennis task depends on the visual information that is processed concerning the approaching object (i.e., the ball). A player who looks in the correct place at the correct time is more likely to predict the ball’s future trajectory and the time of arrival accurately. Second, when attempting to intercept an approaching object, players also have to consider the time latency necessary to adjust motor commands based on the visual information. For example, the opponent must select an appropriate trajectory for the racket based on information available early in the ball flight, and must refine the estimates of ball position and velocity from late ball flight visual information. Third, the complexity of tasks during a table tennis exercise can have an acute effect on both execution and the selection of responses. Reducing or increasing the amount of time between “what” and “how” decisions by manipulating the ball speed or altering the size or color of the ball can have a major impact on performance. Fourth, the temporal and spatial characteristics of ball flight also affect response selection and execution. To date, no study has examined these physical and cognitive measures concurrently in a realistic and dynamic-action environment (i.e., table tennis setting); therefore, the present study was partly exploratory in nature.

We examined the effects of a 12-week (twice per week, 70 min per session) table tennis training program on the motor skills and executive functions of children with ADHD. We tested their motor skills by using the Test of Gross Motor Development–2 (TGMD-2; Ulrich, 2000) and assessed their executive functions by using two measures of response inhibition: the Stroop Color and Word Test (Golden, Freshwater, & Golden, 2003), where interference by a prepotent response that is no longer the required response (response conflict) indicates a lack of inhibition; and the computer version of the WCST (Heaton & PARStaff, 2003), in which response perseveration indicates poor inhibitory control. Based on the limited data available from previous research, we hypothesized that children with ADHD participating in the table tennis training program would demonstrate an improvement and yield greater positive changes in motor skills and executive functions compared with those not participating in the intervention.

Method

Participants

The participants recruited for the study included three groups of children (all boys) between the ages of 7 and 12 years: Groups 1 and 2 involved children diagnosed with ADHD (ADHD training, n = 15; ADHD non-training, n = 15), and Group 3 involved TD children without ADHD (TD non-training, n = 30).

Children with ADHD were recruited from local pediatric services and primary schools as well as through a media release. For inclusion in the study, children had a formal and unambiguous diagnosis of ADHD made by a psychiatrist or a pediatrician using recognized diagnostic procedures (i.e., meeting the criteria for ADHD as defined in the Diagnostic and Statistical Manual of Mental Disorders [4th ed.; DSM-IV; APA, 1994]). Children with comorbid conditions that commonly coexist with ADHD (e.g., oppositional defiant disorder) were included if ADHD was the primary diagnosis. However, children diagnosed with major neurodevelopmental or psychiatric disorders (e.g., autism spectrum disorder, intellectual disability, and cerebral palsy) were excluded. At the end of the recruiting process, two children were diagnosed with associated conditions such as oppositional defiant disorder; the ADHD participants lacked other psychiatric disorders.

In addition to the formal diagnosis made by a pediatrician or psychiatrist, the primary caregiver confirmed the presence of the severity of ADHD symptoms a priori by using the Chinese version of the ADHD test (Cheng, 2008) originally developed by Gilliam (1995), and the Chinese version of the Child Behavior Checklist (CBCL; Chen, Huang, & Chao, 2006; that is, ratings above the clinical cutoff, t value ≥ 70 on the DSM-IV subscales of the CBCL) originally developed by Achenback and Rescorla (2001). Selected children were included in the study, regardless of their medication status. The parents were asked to maintain the consistency of the type and dose of medication throughout the course of the intervention, and therefore, we did not control the medication type and dose amount used by the children.

The children in Group 3 were recruited from the overall community through word of mouth as well as through faculties at the universities and public schools. The parentally provided history did not show any evidence of hyperactive or impulsive behavior, ADHD, and reading disabilities. None of the children in Group 3 were reported to be on any type of medication. The project was approved by the National Cheng Kung University Research Ethics Committee for Human Behavioral Sciences. The parents as well as their children signed informed consent forms. The participants’ demographic information is listed in Table 1.

Table 1.

Participant Demographic Characteristics.

	ADHD training (n = 15)		ADHD non-training (n = 15)		TD non-training (n = 30)		F	p
	M	SD	M	SD	M	SD	F	p
Age (years)	9.08	1.43	8.90	1.66	9.14	1.54	0.12	.89
Height (cm)	134.35	11.55	134.00	9.97	135.52	12.27	0.11	.90
Weight (kg)	32.30	10.61	32.89	9.60	35.14	11.21	0.44	.65
BMI (kg/m²)	17.55	4.00	18.14	4.24	18.78	4.00	0.48	.62
ADHD Q (n, %)
≥131	0		0
121-130	1		1
111-120	0		0
90-110	7		7
80-89	5		5
70-79	1		1
≤69	1		1
Medicine intake (n, %)
None	6 (40%)		6 (40%)
Yes	9 (60%)		9 (60%)

Note. BMI = body mass index; Q = quotient, the higher the quotient lead levels the more severe.

Physical Exercise Intervention Program

We conducted the table tennis program merging physical and cognitive training over 12 consecutive weeks in the gymnasium of the primary researcher’s university. It was held two times a week for 70-min periods on weekends. The primary researcher supervised all the sessions. The sessions included a warm-up (5 min), basic table tennis skill and teaching progression (20 min), executive function training through table tennis exercise (20 min), group games and conditioning (20 min), and a cool-down (5 min). The main objective was to promote motor skills and executive functions.

Under the first main session of the program (20 min), basic table tennis skills were taught progressively over the whole training session and contained the following main components: (a) ball- and racquet-handling drills, (b) forehand and backhand counterstroke, (c) forehand and backhand block, (d) forehand and backhand attack, (e) serve (basic forehand and backhand serve), (f) return shot (basic forehand and backhand return; continuously hitting back a ball delivered at the same speed, and from the same direction, either by the coach or by the automatic ball projection machine), (g) proper footwork and movement (e.g., ready position, as well as one-, two-, and cross-step), and (h) comprehensive practice.

For the second main session of the program (20 min), the skills of executive function training with table tennis exercise were taught to concentrate on a particular task and practice specific skills assumed to be related to executive functions. Two training programs were adopted in this session. First, every child practiced hitting back the ball, during which the interval, direction, and speed of the balls served by the coach or the automatic ball projection machine varied to provide varying levels of complexity. Second, the coach and research assistants manipulated three conditions for the children in hitting back (Tsai, 2009): (a) white balls projected from fixed or random directions or heights, (b) white and orange balls projected randomly from a specified direction, and (c) white and orange balls projected randomly from uncertain directions as well as at uncertain times, to hinder any prediction of the following occurrence. In addition, the first condition could be manipulated to enable only an odd number of balls from a fixed direction to be hit, during which the participants would read these numbers aloud. Moreover, the second or third condition could be manipulated to enable only the orange ball to be hit, so that the children could inhibit their movement programming when a white one was projected, and vice versa. Consequently, each child would prepare to respond by processing actual visual information, planning his response, and then programming the appropriate action or inhibition response. The intervention complexities of inhibitory control and attention training were tailored to the individual needs and motor skill levels of each child. All of the training prescriptions were structured to achieve a particular type of training we believed would be related to inhibitory control and attention. We adopted the training protocols mainly from previous studies (Tsai, 2009; Tsai, Wang, & Tseng, 2012); a more detailed training manual is available on request from the primary researcher.

Under the third main session of the program (20 min), group games and conditioning, the coach led the group games, and focused on gross and fine motor control as well as sportsmanship. For example, the purpose of the table tennis balancing shuttle-run competition was to promote endurance as well as body coordination and fundamental motor skill development, during which the participants held a table tennis ball on a paddle while walking fast or running back and forth across a distance of 5 m, and passed the paddle and the table tennis ball to the next person on the same team. If the table tennis ball fell, then the participant restarted walking or running from where the ball fell, and began the contest from that position, and all team members who completed balancing the ball within the shortest time were considered the winners. Conducting such group games could comprise a fun part of practice, and children could be trained to exhibit sportsmanship with teammates and opponents at all times. Other fun and challenging activities such as running, wind sprints, jumping rope, and line jumps can improve a child’s overall fitness, thereby assisting in his table tennis game.

Pre–Post Program Measures of Motor Skill and Executive Function Tests

TGMD-2

We assessed the motor skills by using the TGMD-2 (Ulrich, 2000). This test comprises two subtests, and evaluates six locomotor and six object-control skills. The tasks were run, gallop, hop, leap, jump, and slide for the locomotor skills, and bat, dribble, catch, kick, throw, and roll for the object-control skills. Each skill includes three to five performance criteria for describing performance qualitatively. Individual performance criteria are scored with a 1 or 0 to indicate the presence or absence, respectively, of a skill component. A raw score of 24 on locomotor items and of 24 on object-control items is a perfect score. Because each participant is required to execute each skill twice, the highest total subtest raw score for the locomotor as well as object-control skills is 48 points. The TGMD-2 is a norm- and criterion-referenced test that assesses the gross motor ability of children aged 3 to 10 years, and has shown evidence of validity and reliability among children.

Stroop Color and Word Test

We adopted the children’s version of the Stroop Color and Word Test for ages 5 to 14 years to measure the executive function in our participants (Golden et al., 2003), and it was first described by Golden (1975). The Stroop is a classic task of response inhibition that requires participants to name the color of written words, concurrently ignoring the word representing the color itself (e.g., “red” and “blue”). This Stroop test version consists of three subtasks (i.e., Word, Color, and Color–Word), and each subtask comprises 100 stimuli distributed evenly in five columns containing 20 items each. The first subtask shows the color words in random order (“red,” “green,” and “blue”) printed in black ink on a white 8.5″ × 11″ sheet of paper. The second subtask displays solid-color rectangles in one of the three mentioned basic colors. The third subtask contains words printed in an incongruous ink color (e.g., the word “green” printed in red).

The participants were instructed to read the words, name the colors, and finally, name the ink color of the printed words as quickly and as accurately as possible in the three subsequent subtasks from top to bottom (20 trials), and from left to right (comprising five columns). For any mistake, the participants were asked to stop, and proceed only after correcting the mistake. We used the number of correct items completed in 45 s on each subtask for the analyses, with more items indicating greater performance. The dependent variables were the raw scores for the Color–Word conditions because the Word and Color subtask scores are not measures of executive functioning.

WCST

We also used the computer version of the WCST for assessing executive functions (Heaton & PARStaff, 2003). The WCST includes 4 stimulus cards and 128 response cards. The stimuli cards display one red triangle, two green stars, three yellow printed crosses, or four blue circles. The 128 response cards contain pictures combining various forms (triangles, stars, crosses, and circles), colors (red, blue, yellow, and green), and printed numbers (one, two, three, or four). In the computer version of the WCST, the cards are displayed on a computer screen. The four stimuli cards are identical to the card version, except that the participants were required to choose a response card to match one of the four key cards based on its potential characteristics. We used this computerized WCST version to reduce the complexity of WCST administered and to increase the efficiency of data collection. We used six raw scores from the WCST indices for analysis: total correct, perseverative responses, perseverative errors, non-perseverative errors, conceptual-level response, and categories completed.

Procedure

Once we received ethical approval, we contacted the parents whose children met the inclusion criteria to administer the 12-week-long two 70-min intervention sessions. Immediately before and after the 12-week intervention, we contacted the parents of the children in each group, and scheduled them for pre-tests and post-tests at their convenience. We assessed each participant on 2 days: 1 day for the motor skill tests and the other for the executive function measures. We conducted motor and executive function performance tests within 2 weeks before and after the training program. The participants were informed not to engage in intense physical activity on the day of the executive function tests.

For the primary pre- and post-intervention assessments, we recorded the measurements of weight and height (to the nearest 0.1 kg and 0.1 cm, respectively) by using a bioelectrical impedance analyzer (MF-BIA8, InBody 720, Biospace). We administered two measures of executive functions in random order, and each participant was, respectively, tested in three rooms by three trained research assistants. All test directions were followed precisely, and all the children completed all of the measures pertaining to the executive function assessments. The testing duration was approximately 25 to 35 min per child. The TGMD-2 was administered to all the children in an isolated gymnasium, where the primary researcher worked with the trained research assistants. To ensure assessment accuracy, all sessions were videotaped. Each child received verbal descriptions and demonstrations before the tests. They performed at their own pace and were not unduly coerced to move quickly. We provided the participants with additional directions if they did not seem to understand the directions the first time. All the test directions were followed precisely, and all participants completed the motor skill assessments. The testing duration was approximately 20 to 40 min per child.

Interrater reliability for the TGMD-2 test was established by two observers trained by the primary researcher. Training consisted of two previously videotaped elementary school-aged boys with and without ADHD demonstrating the skills required for the TGMD-2, and the observers indicated the strengths and weaknesses of their performance. The primary researcher and the observers engaged in substantial discussions on specific topics to observe each skill. The raters were allowed to replay the recordings, to complete their ratings. Interrater reliability was then obtained from the videotaped TGMD-2 trials of all the children with ADHD and those without disabilities. We devised a checking system to maintain a >.85 rater agreement to control for potential errors related to experimenter drift.

We conducted the physical exercise program in a consistently available table tennis classroom in the primary researcher’s university. One coach and six research assistants trained in physical education as well as one research assistant in special education administered the interventions. Before the study, we held a workshop to introduce the physical exercise program to all of the parents and children with ADHD, and provided a written treatment protocol to the coach and the seven research assistants. The coach, an undergraduate student in the Department of Physical Education, had been an elite national table tennis player for 5 years, and had 5 years of experience teaching table tennis to children with and without disabilities. All of the research assistants had experience working with children with ADHD, and were undergraduate students majoring in physical education or special education, or were graduate students majoring in adapted physical education. The 12-week physical exercise program comprised 24 sessions (2 sessions per week, 70 min per session). During each session of the first two 20-min training sessions, two children with ADHD were always paired with the same research assistant to practice their skills throughout the entire intervention period. The primary researcher supervised all of the sessions to ensure adherence to the treatment protocol.

Statistical Analysis

We calculated the means and standard deviations for all of the variables. The analyzed dependent variables were the TGMD-2 (locomotor and object-control skills), Stroop Color–Word condition, and WCST performance (total correct, perseverative responses, perseverative errors, non-perseverative errors, conceptual-level response, and categories completed).

We tested the initial differences among the three groups for the mean scores of all of the dependent variables by conducting a one-way ANOVA. To assess the effects of the physical exercise program, we conducted ANOVA with a 2 (time: pre-test vs. post-test) × 3 (group: ADHD training vs. ADHD non-training vs. TD non-training) mixed-model factorial design. We performed Tukey’s post hoc test if significant group differences emerged. We followed up with the tests of simple main effects, with significant interaction effects. The effect size was computed and reported as a partial η² value for the ANOVA evaluations.

To quantify the magnitude of changes in the dependent variables between the pre- and post-assessment scores within the groups, we calculated the effect sizes (Cohen’s d) by dividing the mean change in a test score by the standard deviation of the test score at baseline to quantify the magnitude of change between scores. We conducted all analyses by using SPSS version 18.0 for Windows, and the level of significance was set at p < .05.

Results

Table 2 shows the means, standard deviations, and effect sizes (Cohen’s d values) for the pre- and post-training measures of the three groups, and Table 3 lists the results of two-way mixed-factorial-design ANOVA. No significant differences emerged among the groups for all dependent variables at baseline. We observed significant group-by-time interaction effects on both TGMD-2 subtests, Stroop Color–Word condition, and WCST performances in total correct, perseverative errors as well as the categories completed.

Table 2.

Means, Standard Deviations, and ES Values for the Motor and Cognitive Variables.

Variables	ADHD training (n = 15)			ADHD non-training (n = 15)			TD non-training (n = 30)
Variables	Pre-test	Post-test	ES	Pre-test	Post-test	ES	Pre-test	Post-test	ES
TGMD-2
Locomotor	38.20 (2.70)	43.33 (2.50)	1.90^a	38.13 (3.56)	40.00 (4.02)	0.53 ^b	39.00 (3.05)	43.63 (2.70)	1.52 ^a
Object control	40.07 (1.71)	45.27 (1.94)	3.04^a	40.60 (3.11)	40.60 (3.91)	0.00	42.00 (2.92)	44.23 (2.84)	0.76 ^b
Stroop
Color–Word (+)	23.73 (4.23)	32.47 (2.75)	2.07^a	23.47 (2.92)	24.27 (5.47)	0.27^c	28.10 (10.04)	32.40 (8.96)	0.43^c
WCST
Total correct (+)	71.33 (9.22)	82.27 (10.89)	1.19^a	71.93 (13.27)	72.47 (6.45)	0.04	75.37 (12.89)	76.27 (11.03)	0.07
Perseverative responses (−)	23.33 (13.42)	18.00 (13.44)	0.40^c	25.60 (19.84)	14.53 (11.36)	0.56^b	22.93 (12.84)	15.87 (10.53)	0.55^b
Perseverative errors (−)	27.13 (12.02)	16.20 (10.85)	0.91^a	22.47 (16.21)	20.27 (14.23)	0.14	20.30 (10.28)	17.13 (11.91)	0.31^c
Non-perseverative errors (−)	19.00 (9.02)	12.00 (7.35)	0.78^b	18.00 (8.25)	13.40 (7.86)	0.56^b	21.20 (12.00)	15.50 (9.15)	0.48^c
Conceptual-level response (+)	62.20 (16.75)	78.20 (13.04)	0.96^a	60.07 (16.81)	69.67 (13.37)	0.57^b	63.23 (18.46)	68.80 (14.10)	0.30^c
Categories completed (+)	4.00 (1.81)	5.60 (1.06)	0.88^a	4.00 (1.60)	4.67 (1.23)	0.42^c	4.30 (1.88)	5.07 (1.55)	0.41^c

Note. ES = effect size (Cohen’s d). (+) = higher scores represent better performance; (−) = lower scores represent better performance. TD = typically developing; TGMD-2 = Test of Gross Motor Development–2; WCST = Wisconsin Card Sorting Test.

A Cohen’s d value ≥0.8 indicates a large ES.

A Cohen’s d value ≥0.5 < 0.8 indicates a medium ES.

A Cohen’s d value ≥0.2 < 0.5 indicates a small ES.

Table 3.

Two-Way ANOVA With Repeated Measures on Time (Pre-Test vs. Post-Test).

Variables	F	p	Partial η²	Observed power
TGMD-2 locomotor
Group (G)*	3.35	.04	.11	0.61
Time (T)**	112.22	.00	.62	1.00
G × T**	6.86	.00	.19	0.91
TGMD-2 object control
Group (G)*	4.64	.01	.14	0.76
Time (T)**	75.66	.00	.57	1.00
G × T**	23.37	.00	.45	1.00
Stroop Color–Word
Group (G)*	4.87	.01	.15	0.78
Time (T)**	23.78	.00	.29	1.00
G × T*	4.92	.01	.15	0.79
WCST total correct
Group (G)	1.15	.32	.04	0.24
Time (T)*	5.11	.03	.08	0.60
G × T*	3.24	.04	.10	0.60
WCST perseverative responses
Group (G)	0.06	.94	.00	0.06
Time (T)**	23.18	.00	.29	1.00
G × T	0.93	.40	.03	0.20
WCST perseverative errors
Group (G)	0.47	.63	.02	0.12
Time (T)**	14.70	.00	.21	0.97
G × T*	3.44	.04	.11	0.62
WCST non-perseverative errors
Group (G)	.84	.44	.03	0.19
Time (T)**	19.47	.00	.26	0.99
G × T	0.24	.79	.01	0.09
WCST conceptual-level response
Group (G)	0.65	.53	.02	0.15
Time (T)**	25.41	.00	.31	1.00
G × T	2.38	.10	.08	0.46
WCST categories completed
Group (G)	0.41	.66	.01	0.11
Time (T)**	41.24	.00	.42	1.00
G × T*	3.19	.04	.10	0.59

Note. TGMD-2 = Test of Gross Motor Development–2; WCST = Wisconsin Card Sorting Test.

p < .05. **p < .01.

Effect of the Physical Exercise Intervention Program on the TGMD-2 Test

Because significant interaction effects emerged for both the locomotor and object-control scores (Table 3), we conducted a follow-up of the simple main effects to understand the group-by-time interaction. There were significant differences among the three groups for both the locomotor (F = 7.68, p < .01) and object-control (F = 10.76, p < .01) skills after the intervention. The ADHD training group exhibited improved locomotor (+3.33) and object-control (+4.67) skills after the physical exercise program compared with the ADHD non-training group (Figure 1). The TD non-training group also demonstrated an enhanced performance on the locomotor (+3.63) and object-control (+3.63) skills after the 12-week intervention compared with the ADHD non-training group. We did not observe any group differences for both locomotor (F = 0.54, p = .59) and object-control (F = 2.94, p = .06) skills before the intervention.

Figure 1.

TGMD-2 raw scores as functions of group and time on (a) locomotor subtest and (b) object-control subtest.

The simple-main-effects results also revealed significant differences before and after the intervention within each group for both the locomotor and object-control skills. The ADHD training group exhibited significant improvements in the locomotor (+5.13; F = 89.64, p < .01) and object-control skills (+5.20; F = 156.00, p < .01) after training. We observed large effects for the locomotor (Cohen’s d = 1.90) and object-control (Cohen’s d = 3.04) subtest scores (Table 2). The ADHD non-training group demonstrated a significantly improved performance (+1.87) on locomotor skills (F = 26.39, p < .01, Cohen’s d = 0.53) after the intervention, but not on object-control skills (F = 0.00, p = 1.00). The TD non-training group exhibited a significantly improved performance on both the locomotor (+4.63; F = 57.83, p < .01, Cohen’s d = 1.52) and object-control (+2.23; F = 27.58, p < .01, Cohen’s d = 0.76) skills after the intervention.

Effect of the Physical Exercise Intervention Program on the Stroop Test

An interaction of the group-by-time effect was found in the Stroop Color–Word condition (Table 3), and we used a follow-up of the simple main effects to understand the interaction. No group differences were present before the intervention; however, significant differences among the three groups emerged afterward. Figure 2 shows that both the ADHD training (+8.20) and TD non-training (+8.13) groups performed better on the Stroop Color–Word condition compared with the ADHD non-training group for the post-intervention (F = 7.47, p < .01). Regarding within-group differences before and after the intervention, both the ADHD training (+8.73; F = 172.35, p < .01, Cohen’s d = 2.07) and TD non-training (+4.30; F = 6.50, p < .05, Cohen’s d = 0.43) groups exhibited significant improvements in the Stroop Color–Word condition score compared with the ADHD non-training group after the intervention, whereas the ADHD non-training group performed similarly at baseline and after the intervention period (F = 0.74, p = .41).

Figure 2.

Stroop Color–Word score as a function of group and time.

Effect of the Physical Exercise Intervention Program on the WCST

We noted interactions in group-by-time differences for total correct, perseverative errors, and categories completed (Table 3), and we conducted a follow-up of the simple main effect to understand the group-by-time interaction for each significant dependent variable. No group differences emerged for total correct (F = 0.71, p = .50), perseverative errors (F = 1.52, p = .23), and categories completed (F = 0.21, p = .81) before the intervention; however, the ADHD training group performed better (+9.80) on the total correct performance (i.e., an indicator of overall WCST performance) compared with the ADHD non-training group (F = 3.65, p < .05) after the intervention (Figure 3a). No significant between-group differences were found for perseverative errors (F = 0.47, p = .63) and categories completed (F = 1.76, p = .18) after the intervention.

Figure 3.

WCST raw scores as functions of group and time on (a) total correct, (b) perseverative errors, and (c) categories completed.

For the within-group differences between pre- and post-training, the ADHD training group exhibited significant improvements (+10.93, Cohen’s d = 1.19) in total correct performance between pre- and post-intervention (F = 13.12, p < .01), whereas the ADHD non-training (F = 0.03, p = .86) and TD non-training (F = 0.11, p = .74) groups performed similarly at baseline and after the intervention period. For the perseverative errors, the ADHD training (−10.93; F = 9.64, p < .01, Cohen’s d = 0.91) and TD non-training (−3.17; F = 8.26, p < .01, Cohen’s d = 0.31) groups exhibited significantly fewer errors after the 12-week training period. For the categories completed, all three groups exhibited significant improvement before and after the intervention (ADHD training: +1.60, F = 27.43, p < .01, Cohen’s d = 0.88; ADHD non-training: +0.67, F = 4.83, p < .05, Cohen’s d = 0.42; TD non-training: +0.68, F = 13.69, p < .01, Cohen’s d = 0.41).

Discussion

The main purpose of the present study was to explore the effects of a 12-week physical exercise intervention on motor skills and executive functions in children with ADHD. Our first hypothesis was that chronic physical exercise would improve motor skills and executive functions for the ADHD training group. Our second hypothesis was that the benefit of chronic physical exercise would be more apparent (i.e., larger effect sizes) for the ADHD training group than those not participating in the intervention. Below, we discuss our results separately for outcomes relate to the TGMD-2, Stroop, and WCST measures.

TGMD-2

With regard to motor skill performance, our results provided partial support for our first hypothesis. Specifically, we found that the locomotor and object-control skills increase for the ADHD children receiving the physical exercise intervention. However, differential improvements on motor skills were also observed for TD and ADHD children not receiving the intervention. Nevertheless, we found greater improvements in both locomotor and object-control skills for children in the physical exercise intervention, relative to those in the control groups. Our second hypothesis was therefore supported.

The observed improvements in motor skills are consistent with those noted in previous studies (Chang et al., 2014; Pan et al., 2017; Smith et al., 2013; Verret et al., 2012), which have demonstrated improvements in motor skills after physical exercise programs. We expected higher scores in locomotor and object-control skills, as assessed using the TGMD-2, which were observed in the ADHD training group, because our physical exercise program was designed to target these variables and to offer optimal improvements. The examples are basic table tennis skills (i.e., object-control skills) as well as proper footwork and movement training (i.e., locomotor skills), in addition to group games such as the table tennis balancing shuttle-run competition, which was included to promote endurance fitness, body coordination, and fundamental motor skills (e.g., walking, running, balancing, and passing the paddle and ball). Because significant motor skill difficulties have been reported in children with ADHD (Fliers et al., 2008; Wilson, 2005), and because motor skills are crucial for achieving sufficient physical activity levels (Barnett, Morgan, Van Beurden, Ball, & Lubans, 2011) as well as for maintaining aspects of health-related physical fitness (Barnett, van Beurden, Morgan, Brooks, & Beard, 2008; Pan et al., 2017) into adulthood (Stodden, Langendorfer, & Roberton, 2009), improvements in motor skills, especially the large effect of changes over time in object-control skills for the ADHD training group, could be a critical variable in facilitating participation in sports for children with ADHD. Such long-term improvements may result in greater participation in competitive sports with peers without disabilities or later participation at recreation centers as adults.

Why improvements were observed in children not receiving the intervention, especially greater improvement for TD children than ADHD non-training group, may be that TD children simply had greater room to improve given their higher organized opportunities for participating in physical exercise or to be active with other children relative to children with ADHD (Harvey et al., 2009). Another possibility may be that children with ADHD are likely to devote little time to acquire the specific details of physical activities, as the inhibitory model of executive functions (Barkley, 1997) would suggest. Furthermore, this could be attributable to the effects of potential maturation or regression to the mean as explanations for our findings. These explanations are admittedly speculative, and future work is required before any definitive conclusions may be drawn.

Stroop Color and Word Test

In support of our first hypothesis, the Stroop Color–Word condition in the ADHD training group improved after training; however, both groups of children not receiving the intervention also improved on the Stroop Color–Word condition. Indeed, we are not able to rule out effects of school training on attention, motivation, and on-task behavior in our participants. It may be that regular school classroom and activities exposed our participants to additional opportunities to learn and practice attentive, motivational, and on-task behavior. This explanation is post hoc and should be considered with caution. Furthermore, examination of effects size within each group revealed a larger improvement in the Stroop Color–Word condition for the ADHD training group than for the children not receiving the intervention. Overall, these results provide supporting evidence regarding the benefit of physical exercise on the Stroop Color–Word performance in children with ADHD, and can be used as a critical reference that should facilitate comparisons between the results of future research and clinical practice in other countries.

Previous studies have provided supporting evidence regarding the positive effect of the current physical exercise program on the Stroop Color–Word condition (i.e., selective attention or the inhibition of a dominant response) that focused on healthy children (Telles, Singh, Bhardwaj, Kumar, & Balkrishna, 2013) and children with ADHD (Chang et al., 2012). Telles et al. (2013) assessed the effects of yoga and physical exercise over 3 months (5 days a week, 45 min each day), and found that both interventions improved Color–Word naming performances. Chang et al. (2012) found that an acute 30-min bout of moderate-intensity treadmill exercise improved the Stroop Color–Word condition in children with ADHD, and suggested that an acute exercise of this type was beneficial for inhibition. That the aforementioned research, in addition to our physical exercise program, was almost comparable in their Stroop results emphasized that physical exercise, regardless of whether it was chronic versus acute or open-skill tasks versus aerobic types of exercise, in some form, is a critical component of the Stroop Color–Word performance. However, longer follow-up studies are necessary to determine whether physical exercise benefits are transient and only persist as long as the exercise continues.

WCST

Our second hypothesis, greater predicted benefit of physical exercise intervention for the ADHD training group, was supported for the WCST results. When collapsed across time and group, there were significant Time × Group interactions for total correct, perseverative errors, and categories completed, indicating larger improvement for ADHD training than ADHD non-training and TD children. These group-by-time interaction effects indicated that three aspects of executive function, as measured using the WCST, improved significantly in the ADHD training group from pre- to post-exercise, and are consistent with the time main effect listed in Table 3. The improved abilities in certain aspects of the WCST were potentially induced by our chronic physical exercise training. The present findings offer some support for the hypothesis that a chronic physical exercise is beneficial to children with ADHD on improving their executive functioning. Although some small-to-moderate effect sizes for improvements in the WCST measure for both the ADHD non-training and TD children, absolute change was substantially greater in the ADHD training group; hence, the change for the ADHD training group is likely to be of greater clinical significance.

The failure of all of the interaction effect to be demonstrated with the WCST task is consistent with past research (Chang et al., 2012), showing that this cognitive task may not be sufficiently sensitive toward the specialty of chronic physical exercise, or that the characteristics of our chronic physical exercise program may not suffice to fully engender exercise-related differences on all aspects of the WCST task. Furthermore, individual differences in regular physical activity, motor skill performance, and overall physical fitness may be crucial mediators for an examination of the relationship between physical exercise and positive outcomes in children. Gapin and Etnier (2010) conducted a cross-sectional correlational study to investigate the relationship between daily MVPA and executive functioning in 18 school-aged boys with ADHD, and found that greater MVPA was associated with a lower Tower of London total move score and a faster execution time, indicative of enhanced performance. Hung et al. (2013) indicated that a higher overall motor ability and object-control skill (i.e., basketball throw for distance) in children with ADHD demonstrated shorter N2 and P3 latencies and a larger P3 amplitude under the No-Go condition as well as behavioral measures (i.e., a faster reaction time and higher accuracy). Pontifex et al. (2011) presented neuroelectric evidence, showing that lower-fit children exhibited a larger N2 amplitude, a smaller P3 amplitude, and longer P3 and N2 latencies relative to higher-fit children, indicating that lower-fit children experience greater response conflict, are less effective in their allocation of attentional resources, and demonstrate delayed stimulus classification and processing speed compared with their higher-fit counterparts. Future research should explore the role of these potential mediators in the relationship between chronic physical exercise and executive function in children with ADHD.

Limitations

Our study has a few limitations that should be addressed. First, the use of the TGMD-2, WCST, and Stroop tests permitted limited assessment of other motor and executive functions. By considering only gross motor skills and two measures of executive functions, the full range of children’s motor skills and executive functions was not assessed or controlled. Second, the medication type and dose amount used by the children with ADHD varied, as did the time of day for testing; thus, the potential stimulatory effect of the medication varied as well. Third, the small sample and limited age range and gender of the participants (all boys) limited the generalizability of the results. Future research is warranted to establish the applicability of our findings to people of both sexes and various ages with a larger sample. Fourth, variations existed among the children with ADHD regarding ADHD subtype classification. Based on parental reporting, 22 had been diagnosed with the combined subtype, 3 with the hyperactive-impulsive subtype, and 5 with the inattentive subtype. Whether the variations among the children regarding ADHD subtype affected the outcome of the study remains unknown. Finally, this study utilized passive control groups and had no control to account for competing effects (e.g., received attention, motivation, on-task behavior, etc.); this might have affected the findings and limited their interpretability or generalizability. Therefore, the results must be regarded as preliminary and require replication; however, they should act as a useful reference for future research on physical exercise training for children with ADHD.

Summary and Conclusion

In summary, this study examined the effect of chronic physical exercise on the TGMD-2, Stroop, and WCST performance in children with ADHD. We anticipated that children with ADHD in the chronic physical exercise training group would improve their motor skills and executive functions compared with an ADHD non-training group and a TD control group. However, this expectation was only partially supported because of inadequate controls and limited measures. The results indicated that implementing chronic physical exercise provided tentative evidence for positive effects on the gross motor skills and some of the executive function performances in the ADHD training group, although it is unclear why one of the two groups who did not receive the intervention would have shown similar improvements. In conclusion, physical exercise appears to be an intervention that does no harm because only positive change was observed from its implementation. The reported preliminary findings suggest the potential use of chronic physical exercise program in children with ADHD, but far more research is necessary before widespread use of such interventions would be warranted.

Footnotes

Acknowledgements

The authors would like to express their gratitude to all the adolescents who participated in this study, teachers and parents of adolescents for their support, and research assistants who helped with data collection and other contributions.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by MOST 103-2410-H-017-026-MY3.

Author Biographies

Chien-Yu Pan, PhD, is a professor of the Department of Physical Education, National Kaohsiung Normal University, Taiwan. She is interested in the development of adapted physical activity program for youths with disabilities and the impacts of physical activity training on motor skills, physical activity and fitness, behavior, and cognitive functions for youths with disabilities, especially autism spectrum disorders (ASD) and ADHD.

Chia-Liang Tsai, PhD, is a professor of the Institute of Physical Education, Health and Leisure Studies, National Cheng Kung University, Taiwan. He is interested in the development of treatment programs for children with developmental coordination disorder, ASD, and ADHD and the influences of treatment programs on motor and cognitive functions in these populations.

Chia-Hua Chu, PhD, is a professor of the Department of Physical Education, National Kaohsiung Normal University, Taiwan. His research focuses on exercise physiology. He is also interested in the effects of physical activity on clinical populations.

Ming-Chih Sung is currently a master student in adapted physical education at the National Kaohsiung Normal University, Taiwan. His research examines how physical activity of youths with disabilities influences their cognitive and behavioral functioning.

Chu-Yang Huang is currently a master student in adapted physical education at the National Kaohsiung Normal University, Taiwan. Her research interests focus on the efficacy of physical exercise interventions for atypically developing populations.

Wei-Ya Ma is currently a master student in adapted physical education at the National Kaohsiung Normal University, Taiwan. Her research addresses physical activity, physical fitness, and executive functions in children with ASD and ADHD.

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