The Effect of Motor Imagery Training on Motor Planning of Children with Developmental Coordination Disorder

doi:10.21203/rs.3.rs-4712125/v1

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The Effect of Motor Imagery Training on Motor Planning of Children with Developmental Coordination Disorder

https://doi.org/10.21203/rs.3.rs-4712125/v1

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Children with Developmental Coordination Disorder (DCD) exhibit deficiencies in motor planning abilities and employ inefficient planning strategies. Motor imagery provides insight into the processes of motor planning and may serve as a beneficial intervention for improving action planning in children with DCD. Therefore, the aim of the present study was to investigate the impact of a motor imagery training program on the motor planning of children with DCD.

Motor imagery training was implemented in two groups of children, one with DCD and one without, and the ability to perform motor imagery was assessed using a task of End State Comfort (ESC). The study was used an experimental design with a pre- post-test design, and the participants included 36 children with DCD aged 7–12 years, randomly distributed into experimental (n = 18) and control (n = 18) groups. The sword task was employed to evaluate action planning in this study. The combined intervention of explicit and implicit imagery was used for the intervention.

Results of repeated measures analysis of variance revealed a significant difference between the control and experimental groups (p = 0.008), indicating that the experimental group demonstrated better planning strategies for the end state comfort compared to the control group.

These findings suggest that motor imagery training have the potential to be beneficial in improving motor planning in children with DCD.

Biological sciences/Psychology/Human behaviour

Health sciences/Diseases/Neurological disorders/Movement disorders

Health sciences/Diseases/Neurological disorders/Neurodevelopmental disorders

Developmental coordination disorder

Motor imagery

Motor planning

Developmental Coordination Disorder (DCD) is a condition that causes children, without any cognitive or neurological impairment, to face difficulties in learning, development, and motor control. During motor activities, they may have weak motor skills compared to their peers, imposing significant limitations on these children. Recently, DCD has gained serious attention from a multitude of specialists, including physicians, psychologists, child specialists, and movement behavior experts. This increasing attention is likely due to the secondary consequences resulting from inefficiencies in these individuals ^1–3. The empirical data indicates that individuals with Developmental Coordination Disorder (DCD) commonly exhibit delays in responsiveness to sensory stimuli, an elevated dependence on visual feedback ⁴, deficiencies in spatial visual processing ⁵, and challenges in coordinating academic activities, including writing, drawing, and fine motor skills⁶. Physically, they lack the necessary readiness and are notably overweight and obese. Consequently, these children encounter difficulties in learning new motor skills and exhibit delays in motor development⁷. these outcomes lead to weakened motor skills and reduced motivation to participate in physical activities. These points underscore the importance of early diagnosis and intervention in this disorder, along with addressing the multifaceted needs of this group of children. Motor control is a process that involves coordinating muscles and joints in the execution of a motor skill. In the performance of motor tasks, the initial selection of the type of gripping is determined by task constraints, goals, and intentions Action planning applies to the processes of selecting movement patterns from among several possible forms of movement to achieve a goal ⁸. Among the most important theories in the area of motor control are the internal models theory, consisting of predictive modeling and inverse modeling. Inverse models have mechanisms for Action planning, while predictive modeling is used for simultaneous and online control and correction of movements (predicting the body state after execution and sensory consequences of the action). Many of movements, including throwing and reaching, require both types of modeling. The initial phase of reach movements is controlled by both mechanisms, and the final phase, which is linked to sensory feedback loops, is controlled by predictive modeling to allow adjustments at the endpoint of the trajectory when movement speed decreases ^9,10. These models provide a framework to ensure the selection of an appropriate movement pattern and facilitate comfortable endstate effects.

One of the methods of evaluating action planning is through selective grasping tasks that facilitate the end state comfort of the action. This effect is related to the tendency to grasp in a way that movements at the endpoint are easily performed, even if comfort during the initiation or throughout the movement is compromised. Razenbam et al. (2001) argued that the state and form of grasping at the endpoint may be determined before the initiation of movements. In reviews conducted by Wilson (2013) and Adams (2014), one of the possible hypotheses for the motor difficulties in children with Developmental Coordination Disorder (DCD) is the weakness in generating and utilizing internal modeling. Consequently, action planning is incomplete, and the individual simultaneously relies on slow feedback control. Such a weakness diminishes the learning ability of children with DCD ^1,7. Longitudinal studies have also shown that motor impairments in these children, likely rooted in internal modeling deficits, lead to the persistence of emotional, social, academic, and learning problems even into adulthood ¹. Motor imagery refers to the ability to represent (modeling) a movement without any overt physical movement. The anticipation of sensory outcomes of visualized actions appears to necessitate the activation of the predictive modeling component of various internal models (8). In typically developing children, the efficiency of motor imagery is associated with a greater tendency to have comfort at the endpoint of the action. Although this association is not observed in children with DCD, when asked to grasp and rotate an object, many of them choose a strategy that involves minimal movement of their hand and minimal rotation at the initiation to avoid discomfort at the endpoint. In sequential tasks, action planning with a precise definition of motor commands from the subset of movements is necessary for predicting sensory outcomes based on them ¹¹. In a study by Stöckel et al. (2012), examining action planning and the development of cognitive representation of grasping in typically developing children aged 7 to 9, it was found that mental representation training of specific grasping states improved the level of comfort at the endpoint in these children ¹². Adams et al. (2017) also indicated, in a longitudinal study on the developmental trajectory of action planning in children with Developmental Coordination Disorder (DCD) compared to typically developing children, the inferiority of children with DCD relative to their age-matched peers. They found that this functional deficit is amenable to improvement over time. Therefore, it seems that training involving action representations, especially motor imagery, with appropriate training programs, may be beneficial for the development of internal modeling and action planning. Motor imagery is considered one of the valid and valuable methods in describing the internal modeling state, and it has been utilized in studies related to children with DCD ^13–15. There is also evidence from studies indicating that the ability of motor imagery is a prerequisite and crucial indicator for the capability to implement concurrent modifications in reching performance in typical individuals ¹⁶ and in children with DCD ¹⁷. Motor imagery, through the anticipatory estimation of limb positions, facilitates the rapid integration of afferent and efferent signals, accelerating the perceptual-motor response. In goal-directed reching actions, if intervention movements are introduced or noticeable changes in the environment are identified by the visual system, the nervous system generates rapid adjustments in the movement trajectory during the flight phase. Concurrent and immediate modifications rely on the individual's ability to compare the potential sensory consequences of the impending action (based on the anticipatory internal model) with actual sensory feedback. In adults, motor imagery has contributed to improving sports performance and enhancing the rehabilitation of individuals with stroke¹⁸. For improving internal modeling in children with DCD, the use of motor imagery training may aid in developing and constructing their motor representations.

Population and Sampling

The current research employed an experimental design utilizing a pretest-posttest design with a control group. The statistical population of the study included students (aged 7–12 years) in the elementary level of government girls' schools in Region 3 of the Education Department in Tabriz during the academic year 1400–1401. The sample size was determined using the G*Power software (3.1 V), considering a minimum power of 80%, a significance level of 5%, and the necessary effect size for repeated measures analysis of variance. The minimum required sample size was identified as 36 participants. Children with developmental coordination disorder (DCD) were identified and selected based on inclusion and exclusion criteria. After identification, each child was randomly assigned to either the experimental or control group, with each group consisting of 18 participants. The criteria for selecting children with DCD, according to DSM-5, involved the initial identification of children with movement problems by teachers (Criterion B - DCM-5), using the PMOQ-T questionnaire with 60 participants. The assessment of the identified children continued using the DCD-Q7 parent form (Criterion C, DCM-5)^19,20. Finally, those children who achieved the necessary scores at this stage (44 participants) were evaluated by the researcher using the MABC-2 test. Children scoring below the 16th percentile on the MABC test (a total of 36 participants) were selected as having DCD ^21,22. Participants had no prior learning, psychological, and neurocognitive disabilities. Children with conditions that could potentially affect their performance were excluded from the study with confirmation from a child and adolescent psychiatrist (Criterion D- DSM-5). All participants had no previous familiarity with the specific tasks in the research. This study protocol was approved by the University of Payame Noor Review Board in accordance with the Declaration of Helsinki and performed in accordance with relevant regulations and guidelines.

Assessments

In this study, the Developmental Coordination Disorder Questionnaire (DCDQ-7), the Perceived Motor Skill Competence Teacher Checklist (PMOQT), and the Movement Assessment Battery for Children (MABC) were used for identifying children with DCD. Additionally, for motor imagery training, the software version of the Hand Rotation task and selected motor imagery training program based on previous studies were employed. To assess the dependent variable of motor planning functions, the task of sword displacement task was utilized to measure the end-state comfort effect.

Developmental coordination disorder questioner

The scale for parental awareness of motor control, gross and fine motor skills, and general coordination in children aged 5 to 15 consists of 15 questions, scored on a 5-point Likert scale. The total score range for this scale is from 15 to 75. According to the DCD-Q7 assessment scores, children aged 7 − 5 years with scores (15–46), children aged 8–9 years with scores (15–55), and children aged 10–15 years with scores (15–57) are classified as having or being susceptible to DCD. The reliability coefficients of this questionnaire, assessed through internal consistency (Cronbach's alpha), and test-retest, are reported as 0.83 and 0.85, respectively. Additionally, concurrent validity is established with two subscales: object manipulation and object control in the Movement Assessment Battery for Children-2, with correlation coefficients of 0.65 and 0.60, respectively^23,24.

Teachers’ movement observation checklist

The checklist comprises 18 items assessing the gross and fine motor skills of 5 to 11-year-old children, utilizing a 4-point Likert scale with a score range of 18–72. The summation of scores derived from the evaluation of teachers, using a percentile system, is followed by an examination of children whose overall assessment scores fall within the percentile range of 100 to 16, indicating their healthy status. Children ranking 15 or lower in percentiles are considered at risk or suspicious. In the normative study conducted on a cohort of 505 male elementary school students and their teachers, the reliability of the assessment was determined to be 0.91²⁵.

Movement assessment battery for children (MABC-2)

This test serves as a tool for identifying movement disorders, particularly diagnosing children with developmental coordination disorder (Henderson, 1992). The assessment evaluates static and dynamic balance skills (single-leg balance, walking on a straight line with heel-to-toe steps, and consecutive jumps), catching and throwing skills (catching a tennis ball and throwing a beanbag), and fine motor skills (placing pins, stringing, and drawing mazes) in children of three age groups: 3–6 years, 7–10 years, and 11–16 years. Raw scores are converted into standard scores, and these are further transformed into overall standard scores and percentile ranks. Individuals scoring below the 15th percentile are considered to have developmental coordination disorder. The test's validity has been reported at 80% in Iran ²⁶.

Hand Rotation Task

This program is primarily designed for assessing the motor imagery abilities of children. In this task, participants decide on the direction of rotation of a stimulus shaped like a hand from different perspectives (front and back). When an individual uses motor imagery to visualize their own hand instead of the target stimulus to determine the direction of hand rotation, it reflects the utilization of motor imagery. To evaluate motor imagery in children, a software program for two-dimensional image rotation of the palm and back of the hand (dimensions 9×8 cm) was created using the standalone-psychopy program. Images were randomly rotated from 0 to 360 degrees with a 45-degree increment¹⁴. Each participant had five initial practice trials and 80 trials for the main test, with ten trials at each angle (0-45-90-135-180-225-270-315 degrees). Finally, the average reaction time for each rotation angle and for each clockwise and counterclockwise condition is calculated for each participant. Data from children who completed at least half of their trials are included in the analysis^14,27.

Sword task for action planning

This assessment is designed to evaluate action planning in children aged 3–12 years. It includes a wooden sword (dimensions: length 18 cm, width 2 cm, thickness 1.2 cm) with a handle of 9.5 cm. The set also comprises a box (dimensions: 271313 cm) featuring a hole (dimensions: 20.8 cm) designed for inserting the sword. Additionally, there is a sheet of paper (3028 cm) with a design featuring six positions for placing the sword. Initially, the sword is placed in the design with six positions. Four of these positions (1, 4, 5, 6 for right-handed individuals and 1, 2, 3, 4 for left-handed individuals) correspond to general and control conditions, while the remaining two positions (2 and 3 for right-handed individuals and 5 and 6 for left-handed individuals) correspond to special conditions. Each participant undergoes one practice trial in position 1 before entering the main test. In the main test, for each position, three random repetitions are performed, totaling 18 trials per participant. In special conditions, achieving the ease of the starting point requires sacrificing the comfortable end position, whereas in control conditions, the ease of the starting point smoothly transitions to the ease of the end position. A comfortable end position is inferred when the sword faces towards the box, while an inappropriate end position is inferred when the sword faces away from the box. Participants are instructed to grasp the sword by its handle and insert it into the hole on the box. Special conditions demand careful action planning. The score for this test is the sum of comfortable posture scores for the end position in both special and control conditions. The test demonstrates a retest reliability coefficient of 0.9 and an interrater reliability coefficient of 0.95 ^14,28,29.

Procedure

Following the selection and random assignment of children with DCD into two experimental groups (motor imagery training) and a control group, each comprising 18 participants, an initial assessment of the action planning abilities of the two groups was conducted during the pre-test phase. The experimental group underwent 8 weeks of motor imagery training, involving two sessions per week, each lasting 30 minutes. The selection of program duration and session frequency was based on previous studies and considerations of student accessibility. Both groups engaged in daily educational activities. The motor imagery training programs employed were the mental rotation exercise for the hand ^15,30,31 and motor imagery exercise ^32,33, consistent with prior research. The latter covered six fundamental skills: catching a tennis ball, throwing a tennis ball, hitting a baseball, jumping in pairs, maintaining a ball on a racket while walking, and placing objects in designated locations based on their shapes. Children were instructed to watch a video demonstration of these skills performed by a peer (expert model) of similar age at least two times. During the video, the instructor provided additional instructional points related to the execution of each skill. After watching each skill, the video was paused, and children were asked to visualize and imagine both their own execution and that of their peer. The video playback speed remained constant for all, with occasional pauses for additional explanations. At the end of each imagery training session, children positioned themselves in the actual execution situation and made two attempts at each skill. Approximately 20 minutes were allocated for practicing this program, with an additional 10 minutes dedicated to mental rotation task practice. The training was conducted individually under the supervision of a coach in a school playroom. Before participating in the training program, informed consent form was obtained from parents of children and necessary approvals were obtained from educational authorities. After the mental imagery exercises, the post-test phase involved re-evaluating the motor planning of both groups.

Statistical Analysis

The independent t-test was utilized to explore differences in age, intelligence quotient (IQ), scores of mABC-2, DCDQ, and PMOQ-T test scores. The Shapiro-Wilk test was employed to assess the normality of the data distribution. Assumptions such as the normality of errors, homogeneity of variances (Levene's test), and independence of errors (Mauchly's test of sphericity) were scrutinized. To examine the research hypotheses during the pre-test and post-test stages, the repeated measures analysis of variance (ANOVA) with a 2-level group factor and a 2-level time factor was applied. The assumptions of this analysis, including normality of error distribution (Shapiro-Wilk test), constant variance of errors (Levene's test), and non-significant correlations among errors (Durbin-Watson and Box's M test for homogeneity of covariance matrices), were verified and satisfied (p > 0.05). All hypothesis tests were conducted at a significance level of 0.05. Statistical analyses were performed using SPSS software (version 26).

Utilizing the independent t-test, it was ascertained that during the pre-test stage, no statistically significant differences existed between the two groups concerning age, percentile rank scores of MABC-2, and scores on the DCDQ and PMOQ-T questionnaires (p > 0.05). The findings of the comparison between the two groups in the pre-test stage for selected indicators are succinctly presented in Table 1.

The p-values obtained from the independent t-test for each variable were greater than 0.05, indicating no significant differences between the experimental and control groups at the pre-test stage for the selected indicators.

Table 1

The results of comparing two experimental and control groups in terms of intelligence quotient, age, mABC-2 test score, DCDQ, and PMOQ-T.
	Group	M ± Sd	df	t	سطح معناداری
MABC-2 percentile score	DCDE	6.95 ± 5.3	34	-1.79	0.08
MABC-2 percentile score	DCDC	5.84 ± 4.1	34	-1.79	0.08
age	DCDE	8.9 ± 1.07	34	0.09	0.09
age	DCDC	8.9 ± 1.2	34	0.09	0.09
scores DCDQ	DCDE	48.4 ± 4.5	34	0.15	0.87
scores DCDQ	DCDC	48.15 ± 5.7	34	0.15	0.87
scores PMOQ-T	DCDE	39.05 ± 5.7	34	-1.46	0.15
scores PMOQ-T	DCDC	41.75 ± 5.9	34	-1.46	0.15
Children with Developmental Coordination Disorder-Control group (DCD-C), children with Developmental Coordination Disorder-Experimental group (DCD-E), Developmental Coordination Disorder Questionnaire (DCDQ), Persian version of movement Observation for Teachers (PMOQ-T), Movement assesment battry for children (mABC-2).

The Effect of a Motor Imagery Training Program on Action Planning

To investigate the effect of motor imagery training program on action planning in two groups (control and experimental), a repeated measures (2x2) analysis of variance was used with between-subjects factor (group) and within-subjects factor (time) in two pre-test and post-test periods. The results, as shown in Table 2 and Fig. 1, indicated significant main effects of group and time, as well as an interaction effect. Using one-way analysis of variance, it was determined that the two groups did not have a significant difference in the pre-test stage (p = 0.325), but in the post-test stage, the experimental group and control group had a significant difference \(\:F\left(\text{1,35}\right)=21.6;P<0.001)\). Additionally, the control group did not have a significant difference between the pre-test and post-test stages (p=0.13), but the experimental group showed significant improvement compared to the pre-test \(\:t\left(17\right)=-5.65\:;P<0.001)\).

Table 2

The results, derived from the analysis of variance with repeated measurements on the dependent variable of action planning, between the two groups across two stages: pre-test and post-test.
		Wilks' Lambda	F	df	Sig	Partial Eta Squared
	group	-	10.3	(1, 34)	.003	.23
action planning	time	.58	24.5	(1, 34)	< .001	.42
	Time*group	.83	6.89	(1, 34)	.013	.16

The p-values obtained from the statistical analyses confirm significant differences, indicating that the motor imagery training program had a notable impact on action planning in the experimental group compared to the control group.

Results and conclusion

The objective of this research was to investigate the impact of Motor Imagery (MI) training on action planning in children with Developmental Coordination Disorder (DCD). To achieve this, the effects of motor imagery training, specifically hand rotation (implicit imagery), combined with explicit motor imagery training, on action planning were examined in two experimental and control groups. The results indicated a significant and positive difference in the action planning ability of the experimental group compared to the control group. It is inferred that a combination of explicit and implicit motor imagery exercises enables children with Developmental Coordination Disorder (DCD) to develop and improve their ability to plan actions and create internal models. Overall, considering the obtained results, we conclude that utilizing the strategy of internal modeling through motor imagery exercises in children with DCD has been developed, and the potential of exercises and interventions related to motor imagery can be harnessed to shape internal representations and enhance action planning in children with DCD. The obtained results align with previous studies, including those by Boviro et al. (2019) and Ebrahimi et al. (2020), serving as evidence for the role of motor imagery exercises in the development of internal modeling and action planning. Boviro and colleagues (2019) utilized explicit motor imagery with instructional guidance, while Ebrahimi and colleagues (2020) employed virtual reality exercises for imagery to study action planning in children with DCD. In the current study, a combination of implicit and explicit motor imagery exercises was used to examine action planning. In typically developing children, it has been demonstrated that the effectiveness of motor imagery is associated with a greater tendency to have comfortable end position of action (action planning) ^8,34. Therefore, it can be inferred that the improvement in action planning functions in children with DCD, under the influence of motor imagery exercises, is linked to the advancement of motor imagery abilities. This activates the predictive modeling cycle through motor imagery, leading to an increase in the comfort effect at the endpoint of the action in the targeted task. In explaining the role of motor imagery training in the development of motor skills learning and enhancement, one can point to the functional equivalence and correlation between motor imagery and actual motor execution. According to the PETTLEP model (Physical, Environment, Task, Timing, Learning, Emotion, Perspective) introduced by Holmes and colleagues in 2001, motor imagery processes share same physiological neural processes with real movements, offering a plausible explanation for the role of imagery in performance improvement. According to the PETTLEP model, for maximum efficacy, motor imagery should encompass seven components: physical presence, environmental similarity, task similarity, timing similarity, matching learning stages, emotional factors, and perspectiv³⁵.

At the neurocognitive level, motor imagery involves common neural networks (premotor and parietal cortex) with regions related to action planning and execution. Motor imagery essentially means internal simulation of actual movements. Motor imagery possesses functional equivalence at neural (activation of motor areas in the frontal, parietal, and premotor regions), behavioral (speed and accuracy trade-off), physiological (heart rate changes), and computational (predictive modeling of sensory outcomes) levels with real movements (40). Internal predictive modeling is considered a computational unit for precise and fast execution. These models encode the dynamics of body segments in relation to the environment and predict the consequences of voluntary actions. It means that by creating a motor command, a copy of it is sent to the predictive model, which is then used to determine the post-execution body state and sensory consequences of the impending action ³⁵. Considering the relationship between motor imagery and motor planning, the overlap of neural structures associated with these processes, and the enhancement of motor imagery ability through motor imagery instructions, it seems that motor imagery training could be an effective intervention strategy in improving action planning skills in children with DCD. Motor imagery, in addition to aiding skill development, reflects an individual's ability to plan movements and use anticipatory internal models ³⁶. One of the challenges faced by children with DCD in anticipatory control is a reduced ability to mentally visualize a motor action from a first-person perspective ³⁷. The use of motor imagery through a first-person perspective encourages the performer to assess task constraints. This enables them to internally represent appropriate bodily states for the task, facilitating the comfort of end position of the action ⁸.

Also, an important part of human interactions includes predicting the actions of others, and according to the framework of predictive processing, inferring the intention and purpose of the observed action by minimizing the prediction error occurs at all levels of the cortical hierarchy during the observation and execution of actions. Mirror neuron systems become active both during the execution and observation of actions, playing a crucial role in these processes.

Mirror neuron systems exist in the premotor areas, subcortical motor areas, and the superior parietal gyrus, with reciprocal connections between them.

Engaging in Purposeful activity training leads to neuroplasticity and changes in brain structures, especially in the frontal, premotor, and parietal regions. Neuroplasticity through the mirror neuron system occurs with real observation and execution. In motor imagery training, individuals activate mirror neurons by observing their own and others' actions and by performing the same actions. This leads to the activation of mirror neurons and the formation and strengthening of representational cycles of actions in similar cortical regions^38,39. There is an association between perception and action.

Comparing mirror neuron activity in two groups of skilled and novice athletes during observation and prediction tasks indicates greater dysynchronization of mu waves (an index of mirror neuron activity) in skilled individuals compared to novices. It seems that the gaining experience in virtual reality environments and self-observation, compared to the control group, results in the enhanced performance of the mirror neuron system, which is effective in predictive motor control. The experience and expertise of individuals lead to differences in the level of mirror neuron activity. Skilled individuals use their internal and predictive models to recognize environmental information, while novices lack such developed internal models. The experience and expertise of individuals result in differences in the level of mirror neuron activity. Skilled individuals utilize their internal predictive models for recognizing environmental information, while novices lack developed internal models ⁴⁰. According to motor learning theory, motor learning and retraining take place when accompanied by repetitive exercises and functional activities in various environmental conditions, along with the provision of appropriate feedback.

The improvement in the performance of children with Developmental Coordination Disorder (DCD) resulting from intervention exercises, such as motor imagery exercises, may be attributed to the repetitive nature of the exercises and the availability of multiple feedback sources. Additionally, the observation and imitation of movements contribute to the plasticity of the nervous system through mirror neurons⁴¹. In the motor imagery task (mental rotation of the hand) used in this study, which involves directionality and judgment of the stimulus type, the ability to represent the expected action coordinates is necessary. The progress of DCD children in the experimental group in the targeted task indicates an increase in the ability to activate mental representations and internal action. It appears that the specific task training leads to the activation of internal representation cycles, which is effective in predictive modeling.

Although the increase in activity of mirror neurons has been inferred in this study to lead to the activation of internal representations, this inference requires further investigation. Considering that cognitive functions may impact internal modeling, future studies are suggested to examine the effects of motor imagery exercises on executive functions and working memory. Additionally, it is recommended to explore the consolidation, transfer, and application of acquired abilities in the daily activities and motor skills of DCD children through motor imagery training. Therefore, based on the conducted studies that refer to the potential for development of internal modeling functions^35,42 and the findings of previous studies ^8,36, as well as the present study on the effectiveness of motor imagery training on action planning in DCD children, it seems that we can utilize the high capacity of motor imagery training implicitly and explicitly. Additionally, by employing PETTLEP imagery model extensively and activating the first-person perspective (resulting in greater activation of mirror neurons), we can improve the action planning ability of children with DCD.

It appears that through motor imagery training, DCD children were able to construct and develop motor representations. Alongside actual execution, they utilized visual and tactile information to make accurate predictions of their movements and reduce prospective planning errors.

In conclusion, based on the results of the current study, it can be inferred that motor imagery training have been effective in improving and maintaining the functions of internal modeling and motor planning in children with Developmental Coordination Disorder (DCD). The progress in internal modeling functions likely contributes to the enhancement of motor control and the performance of skills that depend on such control. Therefore, motor imagery training are recommended as a cost-effective, efficient, and implementable intervention method for children with DCD in both home and educational environments. The findings of this study are crucial for rehabilitation specialists and educational professionals dealing with these children. Given that some previous studies have highlighted the motor skill deficits in children with DCD compared to typical children and the impact of motor imagery training on improving their motor skills, future studies should further investigate the differences between these groups. Additionally, examining the transfer of acquired abilities to daily activities, warrants exploration. Considering that studies in this field are still in their early stages, the obtained results serve as a starting point. Further research in future studies is necessary to confirm and expand upon these findings.

Article Message

The findings of this study demonstrate that combined intervention, incorporating both implicit and explicit motor imagery, have proven effective in enhancing the functions of internal modeling and action planning in children with Developmental Coordination Disorder (DCD). These exercises likely hold potential for improving motor skills and performance, assuming a hypothesis of deficits in internal modeling in children with DCD.

Author Contribution

corresponding author: Methodology, Investigation, Project administration, Writing- Original draft preparation, and Editing

Acknowledgement

I extend my deepest gratitude to my family for their patience, understanding, and encouragement during the demanding phases of this endeavor. Their love and support sustained me through the challenges. I also acknowledge the numerous individuals who provided assistance, resources, and encouragement, contributing in various ways to the completion of this work.

Data Availability

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Adams IL, Lust JM, Wilson PH, Steenbergen B. Compromised motor control in children with DCD: a deficit in the internal model?—A systematic review. Neuroscience & Biobehavioral Reviews 2014;47(225–244, doi:10.1016/j.neubiorev.2014.08.011
Faal R, Ghassemi F. Effects of virtual reality therapy on stroke rehabilitation in upper limbs: Systematic Review and Meta-analysis. The Scientific Journal of Rehabilitation Medicine 2017;6(3):286–302(in persian), doi:10.22037/jrm.2017.110505.1341
Lotfi M, Mohamad Zadeh H, Sohrabi M. Effects of Virtual Reality and Reality Training with and without Auditory Information limitation on Motor Learning Table Tennis Forehand. Motor Behavior 2017;9 (in persian)(
Barnhart RC, Davenport MJ, Epps SB, Nordquist VM. Developmental coordination disorder. Physical Therapy 2003;83(8):722
Lee D, Psotta R, Vagaja M. Motor skills interventions in children with developmental coordination disorder: A review study. European Journal of Adapted Physical Activity 2017;9(2):
Fong S, Lee V, Chan N, et al. Dewey, D., Kaplan, BJ, Crawford, SG, & Wilson, BN (2002). Developmental coordination disorder: Associated problems in attention, learning, and psychosocial adjustment. Human Movement Science, 21, 905–918. Fisher, A., Reilly, JJ, Kelly, LA, Montgomery, C., Williamson, A., Paton, JY, & Grant, S.(2005). Fundamental movement skills and habitual physical. SUPERVISORY AND EXAMINING COMMITTEE 2013;32(108
Wilson PH, Ruddock S, Smits-Engelsman B, et al. Understanding performance deficits in developmental coordination disorder: a meta‐analysis of recent research. Developmental Medicine & Child Neurology 2013;55(3):217–228, doi:10.1111/j.1469-8749.2012.04436.x
Bhoyroo R, Hands B, Wilmut K, et al. Motor planning with and without motor imagery in children with Developmental Coordination Disorder. Acta psychologica 2019;199(102902, doi:10.1016/j.actpsy.2019.102902
Hadnett VE. An investigation examining the effects of specificity within the construct of anxiety on planning and execution of movement. Prifysgol Bangor University: 2015.
Teymuri Kheravi M, Saberi Kakhki A, Darainy M, et al. Motor Control Theories: Providing an Integrated Structural Model Based on Common Concepts. The Neuroscience Journal of Shefaye Khatam 2018;6(3):79–90(in persian)
Johansson RS, Flanagan JR. Coding and use of tactile signals from the fingertips in object manipulation tasks. Nature Reviews Neuroscience 2009;10(5):345
Stöckel T, Hughes CM, Schack T. Representation of grasp postures and anticipatory motor planning in children. Psychological research 2012;76(6):768–776
Ter Horst AC, Van Lier R, Steenbergen B. Mental rotation task of hands: differential influence number of rotational axes. Experimental Brain Research 2010;203(2):347–354
Adams ILJ, Lust JM, Wilson PH, Steenbergen B. Development of motor imagery and anticipatory action planning in children with developmental coordination disorder – A longitudinal approach. Human Movement Science 2017;55(296–306
Adams IL, Lust JM, Wilson PH, Steenbergen B. Testing predictive control of movement in children with developmental coordination disorder using converging operations. British journal of psychology 2016;108(1):73–90, doi:10.1111/bjop.12183
Hyde C, Wilmut K, Fuelscher I, Williams J. Does implicit motor imagery ability predict reaching correction efficiency? A test of recent models of human motor control. Journal of motor behavior 2013;45(3):259–269
Fuelscher I, Williams J, Enticott PG, Hyde C. Reduced motor imagery efficiency is associated with online control difficulties in children with probable developmental coordination disorder. Research in developmental disabilities 2015;45(239–252, doi:10.1016/j.ridd.2015.07.027
Adams I. Predictive motor control in children with developmental coordination disorder: Mechanisms and intervention. [Sl: sn]: 2018.
Cools W, De Martelaer K, Samaey C, Andries C. Movement skill assessment of typically developing preschool children: A review of seven movement skill assessment tools. Journal of sports science and medicine 2009;8(2):154–168
Smits-Engelsman B, Schoemaker M, Delabastita T, et al. Diagnostic criteria for DCD: past and future. Human movement science 2015;42(August 2015):293–306
Salehi H, Bakhshayesh R, Movahedi A, Ghasemi V. Psychometric Properties of a Persian Version of the Developmental Coordination Disorder Questionnaire in boys aged 6–11 year-old. Psychology of Exceptional Individuals 2016;1(4):135–161.(in persian)
Badami R, Nezakatalhossaini M, Rajab f, Jafari M. Validity and Reliability of Movement Assessment Battery for Children (M-ABC) in 6-Year-Old Children of Isfahan City. Journal of Motor Learning and Movement 2015;7(1):105–122(in persian)
zarezade m, sahebozamani m, Farahmand s. prevalence of developmental coordination disorder in female 9 to 11 years of Fars Province: (khorrambid city). Journal of Exceptional Education 2016;9(137):27–33(in persian)
Snapp-Childs W, Fath AJ, Watson CA, et al. Training to improve manual control in 7–8 and 10–12year old children: Training eliminates performance differences between ages. Human movement science 2015;43(90–99
Salehi H, Zarezadeh M, Salek B. Validity and Reliability of the Persian Version of Motor Observation Questionnaire for Teachers (PMOQ-T). Iranian Journal of Psychiatry and Clinical Psychology 2013;18(3):211–219(in persian)
Akbaripour R, Daneshfar A, Shojaei M. Reliability of the Movement Assessment Battery for Children - Second Edition (MABC-2) in Children Aged 7–10 Years in Tehran. The Scientific Journal of Rehabilitation Medicine 2018;7(4):90–96, doi:10.22037/jrm.2018.111121.1776
Butson ML, Hyde C, Steenbergen B, Williams J. Assessing motor imagery using the hand rotation task: Does performance change across childhood? Human movement science 2014;35(50–65, doi:10.1016/j.humov.2014.03.013
Jongbloed-Pereboom M, Spruijt S, Nijhuis-van der Sanden MW, Steenbergen B. Measurement of action planning in children, adolescents, and adults: a comparison between 3 tasks. Pediatric Physical Therapy 2016;28(1):33–39, doi:10.1097/PEP.0000000000000211
Craje C, Aarts P, Nijhuis-van der Sanden M, Steenbergen B. Action planning in typically and atypically developing children (unilateral cerebral palsy). Research in developmental disabilities 2010;31(5):1039–1046, doi:10.1016/j.ridd.2010.04.007
Toussaint L, Tahej P-K, Thibaut J-P, et al. On the link between action planning and motor imagery: a developmental study. Experimental brain research 2013;231(3):331–339, doi:10.1007/s00221-013-3698-7
EbrahimiSani S, Sohrabi M, Taheri H, et al. Effects of virtual reality training intervention on predictive motor control of children with DCD–A randomized controlled trial. Research in developmental disabilities 2020;107(103768
Wilson PH, Thomas PR, Maruff P. Motor imagery training ameliorates motor clumsiness in children. Journal of Child Neurology 2002;17(7):491–498
Wilson PH, Adams ILJ, Caeyenberghs K, et al. Motor imagery training enhances motor skill in children with DCD: A replication study. Research in Developmental Disabilities 2016;57(54–62, doi:10.1016/j.ridd.2016.06.014
Fuelscher I, Williams J, Wilmut K, et al. Modeling the maturation of grip selection planning and action representation: Insights from typical and atypical motor development. Frontiers in psychology 2016;7(108
Adams IL, Steenbergen B, Lust JM, Smits-Engelsman BC. Motor imagery training for children with developmental coordination disorder–study protocol for a randomized controlled trial. BMC neurology 2016;16(1):5, doi:10.1186/s12883-016-0530-6
Reynolds JE, Licari MK, Elliott C, et al. Motor imagery ability and internal representation of movement in children with probable developmental coordination disorder. Human movement science 2015;44(287–298, doi:10.1016/j.humov.2015.09.012
Gabbard C. Studying action representation in children via motor imagery. Brain and Cognition 2009;71(3):234–239, doi:10.1016/j.bandc.2009.08.011
Wuang Y-P, Chiang C-S, Su C-Y, Wang C-C. Effectiveness of virtual reality using Wii gaming technology in children with Down syndrome. Research in developmental disabilities 2011;32(1):312–321, doi:10.1016/j.ridd.2010.10.002
i Badia SB, Morgade AG, Samaha H, Verschure P. Using a hybrid brain computer interface and virtual reality system to monitor and promote cortical reorganization through motor activity and motor imagery training. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2013;21(2):174–181
Denis D, Rowe R, Williams AM, Milne E. The role of cortical sensorimotor oscillations in action anticipation. Neuroimage 2017;146(1102–1114, doi:10.1016/j.neuroimage.2016.10.022
MEDICA EM. Is virtual reality effective in improving the motor performance of children with developmental coordination disorder? A systematic review. European journal of physical and rehabilitation medicine 2018;
Hyde C, Fuelscher I, Buckthought K, et al. Motor imagery is less efficient in adults with probable developmental coordination disorder: Evidence from the hand rotation task. Research in developmental disabilities 2014;35(11):3062–3070, doi:10.1016/j.ridd.2014.07.042

No competing interests reported.

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The Effect of Motor Imagery Training on Motor Planning of Children with Developmental Coordination Disorder

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Abstract

Figures

Introduction

Methodology

Population and Sampling

Teachers’ movement observation checklist

Movement assessment battery for children (MABC-2)

Hand Rotation Task

Sword task for action planning

Procedure

Statistical Analysis

Results

Results and conclusion

Conclusion

Declarations

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

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Version 1