Relationship between motor skill competency and executive function in children with Down's syndrome.

bs_bs_banner

Journal of Intellectual Disability Research 860

doi: 10.1111/jir.12189

volume 59 part 9 pp 860–872 septemBer 2015

Relationship between motor skill competency and executive function in children with Down’s syndrome N. Schott & B. Holfelder Department of Sport & Exercise Science, University of Stuttgart, Stuttgart, Germany

Abstract Background Previous studies suggest that children with Down’s syndrome (DS), a genetically based neurodevelopmental disorder, demonstrate motor problems and cognitive deficits. The first aim of this study was to examine motor skills and executive functions (EFs) in school-age children with DS. The second aim was to investigate the relationship between these two performance domains. Methods The Test of Gross Motor Development (TGMD-2), the Movement Assessment Battery Children-2 checklist (MABC2-checklist) and the Trail-Making Test for young children (Trails-P) were used to assess motor and cognitive performances of 18 children (11 boys, 7 girls) with DS aged between 7 and 11 years (9.06 ± 0.96) and an age- and sex-matched sample of 18 typically developing (TD) children (11 boys, 7 girls; 8.99 ± 0.93). Results Individuals with DS showed the expected difficulties in attentional control, response suppression and distraction, as well as in locomotor and object control skills, as indicated by poorer performance than TD individuals. Motor performance (bottom-up as well as top-down measures) and EF correlated positively, with regard to the group with DS only though. In the most complex task (distracCorrespondence: Dr Nadja Schott, Department of Sport and Exercise Science, University of Stuttgart, Allmandring 28, 70569 Stuttgart, Germany (e-mail: [email protected]).

tion), the children of the DS group achieving lower locomotor scores showed lower efficacy scores on the Trails-P. Additionally, strong relationships were found for the perspective of teachers on all sections of the MABC2-Checklist and EF. Conclusion The findings from this study suggest that children with DS are not only impaired in higher-order EF, but showing also deficits in locomotor and object control skills. This study stresses the importance of early interventions facilitating cognitive abilities and motor skills. Keywords Down’s syndrome, executive function, intellectual disability, motor skill competency, TGMD-2, TMT

Introduction Down’s syndrome (DS) or trisomy 21 is the most commonly identified genetic form of intellectual disability (ID) with estimates of prevalence ranging from 6.6 (England & Wales; Wu & Morris 2013), to 7.7 (the Netherlands; de Graaf et al. 2011) and to 8.3 (US; Presson et al. 2013) people with DS per 10 000 population and 11.2 per 10 000 live births in Europe (Loane et al. 2013). Children with DS face enormous difficulties, such as delays in motor skill development and physical fitness (Palisano et al. 2001; Pitetti et al. 2013), abnormal sensorimotor integration (Carvalho & Vasconcelos 2011), obesity

© 2015 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd

Journal of Intellectual Disability Research

volume 59 part 9 septemBer 2015

861 N. Schott & B. Holfelder • Motor skill competency and executive function in children with Down’s syndrome

(van Gameren-Oosterom et al. 2012), health impairments (Hickey et al. 2012), neurological impairments (Dierssen 2012), delays in speech and language skill development (Kent & Vorperian 2013), practical and social functioning (van Gameren-Oosterom et al. 2013), cognitive limitations (Lott & Dierssen 2010) and an increased risk of developing Alzheimer’s-like dementia with age (Zigman & Lott 2007). Uncoordinated, slower, variable, and hesitant movements, as well as a poor ability of these individuals responding to changes in the environment characterize motor skill competence of children with DS (de Campos et al. 2012). Using different approaches, all studies showed that children with DS aged between 6 and 16 years score lower on fundamental movement skills than their typically developing (TD) peers (Connolly & Michael 1986; Jobling 1998; Volman et al. 2007; Capio & Rotor 2010; Hasan et al. 2012). In a recent study, e.g. 3to 11-year-old children with DS showed an improvement in the qualitative assessment of throwing, catching, jumping, kicking and running; however, no age- and gender-matched control group was included (Capio & Rotor 2010). Volman et al. (2007) observed that children with DS had poor scores on manual dexterity, followed by balance and then ball skills with high interindividual variability. Using the Test of Gross Motor Development-2 (TGMD-2; Ulrich 2000), Hasan et al. (2012) found that children with DS aged between 3 and 10 years scored poorer on the locomotor subtest and average on the object–control subtest being relative to the normative TGMD-2 data. It is generally agreed that motor and cognitive development is closely related having similarly protracted developmental trajectories (Diamond 2000) with well-developed gross motor capacities facilitating children’s cognitive functioning. Westendorp et al. (2011) explain this relationship referring to the role of the cerebellum, a similar developmental timetable with an accelerated development between 5 and 10 years of age for both domains, and several common underlying processes such as sequencing, monitoring and planning. Recent studies have been generally consistent with the view that cognition and especially several components of executive control functioning are compromised in individuals

with DS. However, only few studies have been conducted on children and adolescents with DS examining executive functions (EFs) (Rowe et al. 2006; Lanfranchi et al. 2009, 2010; Borella et al. 2013; Carney et al. 2013; Costanzo et al. 2013) so far. Broadly defined, EF is a term incorporating an extensive set of higher-order operations that organise and regulate goal-directed behaviour within the prefrontal cortex (PFC). There are several domains of EF, including the ability to shift between different mental sets or tasks (‘Shifting’), updating and monitoring of working memory representations (‘Updating’; active maintenance and flexible updating of goal/task relevant information with limited capacity) and selectively attending to stimuli and inhibiting prepotent responses (‘Inhibition’; suppression of actions that are inappropriate in a given context and that interfere with a goal-driven behaviour) (Miyake & Friedman 2012). These domains are separable component processes, but not completely independent though (Diamond 2013). In TD children, there is a significant improvement for inhibition from age 3 to 5; it appears to be followed by less dramatic changes from 5 to 8 years of age and even less change after the age of 8 (although brain maturation continues). The executive component of working memory is sufficiently developed by the age of 6 and shows a linear increase until the age of 14 and a levelling off between the ages of 14 and 15. The ability to shift improves with age; however, the shift cost due to accuracy diminished throughout early adolescence, the switch cost due to reaction time increases until adulthood (for a detailed review, see Best & Miller 2010). In contrast, children with DS show greater impairments in executive working memory tasks, which require a high level of cognitive control (Lanfranchi et al. 2009; Costanzo et al. 2013) when compared to mental age-matched controls [mental age (MA)]. Furthermore, they exhibit poorer response inhibition (Borella et al. 2013) and poorer control of concurrent cognitive tasks (Carney et al. 2013). Evidence for a relationship between motor performance and EF in TD populations has been found in only a small number of studies. Wassenberg et al. (2005) found a positive but small relationship between general cognitive performance and motor performance in a sample of 5- to 6-year-old typically and atypically performing children. Piek et al.




N. Schott & B. Holfelder • Motor skill competency and executive function in children with Down’s syndrome

(2004) examined children aged between 6 and 15 years using the McCarron Assessment of Neuromuscular Development (MAND), a Go/No-Go Task, the Trail-Making/Memory Updating Task and a Goal Neglect Task. The authors found that fine and gross motor skills were significantly associated with attention and performance in a Trail-Making task, a task that involves cognitive control as well as working memory. Rigoli et al. (2012) demonstrated in adolescents, that aiming and catching (but not manual dexterity or balance) of the Movement Assessment Battery for Children-2 (MABC-2) accounted for statistically significant unique variance in both visuospatial and verbal working memory assessed by the Wechsler Intelligence Scale for Children-IV, an N-back task and the inhibition subtest from the NEPSY-II. Additionally, a relationship was found between balancing ability and total errors (a composite score including inhibition and switching errors). There are also some studies suggesting potential interrelations between motor performance and EF in children with atypical development. According to Hartman et al. (2010), the most recent literature suggests that children showing intellectual disabilities experience problems with qualitative motor performance, especially in object control skills and EF. Additionally, they concluded that motor and executive deficits appear to be related and are inextricably intertwined; hence, poorer motor control and performance results in poorer EF and vice versa. As far as we know, motor skill performance from both a bottom-up as well as a top-down perspectives1 (see Brown 2012), EFs and the relationship between the two, have not been examined in children with DS to date. Therefore, the aim of the present study was to investigate in children with DS aged 7–11 years whether specific relationships between different subsets of gross motor skills (i.e. standardised assessment measures of locomotor skills and object control skills), standardised teacher reports of motor skill performance and different 1 The bottom-up approach could be characterised as a performance-based assessment of motor skills with the help of a standardised and norm-referenced test battery. The top-down approach provides information on motor skill level with regard to everyday activities and considers the parents’, caregivers’ and/or the children’s opinions (Brown 2012).

domains of EFs (switch, response suppression, distraction) could be established.

Methods Sample Thirty-six children (DS = 18, TD = 18) from Greece between the ages of 7 and 11 years were included in the study. The participants were matched on age and gender, with both groups consisting of 7 girls and 11 boys with an average age of 9.02 years (SD = 0.94). Participants with DS were recruited from public special education schools in central and western Macedonia, Greece. TD children were recruited through a primary school from the same area. Exclusion criteria for both groups included major health conditions. Using overweight and obesity definitions based upon body mass index (BMI),2 33.3% of the children with DS were above the 95th percentile and thus classified as obese (TD 16.7%), and 11.1% were between the 85th and 95th percentile and classified as overweight (TD 33.3%), χ2(3) = 3.08, P = 0.380. With regard to boys, 22.7% were obese and 31.8% were overweight. With regard to girls, 28.6% were obese and 7.1% were overweight, χ2(3) = 4.41, P = 0.220. Only one child in the DS group reports to be physically active, but 10 children in the TD group [χ2(4) = 14.2, P = 0.007]. Table 1 demonstrates the sample’s characteristics. Informed written consent was obtained from organisations and parents prior to the beginning of testing, and also by the participants themselves, who were told that they could opt out at any time. All procedures were in accordance to the Declaration of Helsinki with ethical standards, legal requirements and international norms.

Materials Motor assessment Test of Gross Motor Development-2 (Ulrich 2000). To evaluate motor performance, we used the second edition of the Test of Gross Motor Development (TGMD-2), which is a criterion- and 2 http://apps.nccd.cdc.gov/dnpabmi/ Calculator.aspx?CalculatorType=Metric.





Gender Age (years) Height (cm) Weight (kg) BMI BMI percentile

DS

TD

Statistical analysis

7 girls, 11 boys 9.06 ± 0.96 133.6 ± 11.1 34.4 ± 11.6 18.9 ± 4.79 62.1 ± 37.7

7 girls, 11 boys 8.99 ± 0.93 137.2 ± 9.7 34.8 ± 10.3 18.2 ± 3.55 62.1 ± 38.1

χ2(1) = 0.00 t(34) = 0.21 t(34) = −1.04 t(34) = −0.12 t(34) = 0.55 t(34) = 0.00

Table 1 Demographics and physical characteristics

BMI, body mass index; DS, Down’s syndrome; TD, typically developing children.

norm-referenced test designed to assess gross motor functioning of children aged 3–10 years (Ulrich 2000). The test measures 12 gross motor skills that are usually acquired by children in preschool and early elementary grades. They are subdivided into two skill domains: locomotor (LM; running, galloping, hopping, leaping, horizontal jumping and sliding) and object control (OC; striking, bouncing, catching, kicking, throwing and rolling). Each skill was executed twice. Participants’ performances were videotaped with a digital camera that allowed us to analyse movement sequences separately and evaluated based upon the presence (success; score 1) or absence (failure; score 0) of three to five qualitative performance criteria. The highest total raw score for both subtests is 48. A higher score indicates a better quality of movement pattern. Due to the lack of Greek representative reference data, we only used the raw data for further analysis. The TGMD-2 has good psychometric qualities in order to assess the gross motor skill performance of TD children (Evaggelinou et al. 2002 for a Greek sample; Ulrich 2000 for an American sample) and children with impairments, among which children with mild ID (Simons et al. 2008). In the present study, Cronbach’s alpha for the locomotor subset was α = 0.82 (DS α = 0.73, TD α = 0.72), and for the object control subset α = 0.79 (DS α = 0.59, TD α = 0.01) (Ulrich 2000). Inter-rater agreement of ≥0.80 was found for all 12 components. Movement Assessment Battery Children-2 Checklist (Henderson et al. 2007). The Greek version of the checklist was used in this study (Kourtessis et al., 2003). It was developed to screen children for movement difficulties, primarily in the school context, but can be completed by teachers, parents

or professionals as an informal assessment of motor performance and focuses on how a child manages everyday tasks that are encountered at home and at school. The checklist is designed to identify children with motor difficulties in the age range 5–12 years. The questionnaire comprises thirty questions divided into three sections. The first two sections refer to motor performance and differentiate between movement situations based on the child and the environment: (1) movement in a static and/or predictable environment and (2) movement in a dynamic and/or unpredictable environment. Each section is subdivided into three parts, each containing five items. Section A measures self-care skills, classroom skills and physical education/ recreational skills; section B measures self-care/ recreational skills, ball skills and physical education/ recreational skills. For each item, teachers have to rate the motor competence of a child on a 4-point scale (0 = very well; 3 = not close). The third section (3) relates to non-motor factors that might affect movement, e.g. lack of confidence or impulsiveness. The total motor score (TMS) is the sum of the 30-item scores; the higher the TMS, the poorer the performance. According to the manual of the MABC-2, children with scores at or above 50 are highly likely to have a motor impairment in daily-life, children with scores between 35 and 50 are ‘at risk’ of having a motor impairment, and children with scores up to 35 have no detectable motor impairment. The alpha coefficients of both groups in this study were 0.93 for all 43 items (together), 0.89 for section A (static/predictable), 0.91 for section B (dynamic/unpredictable) and 0.56 for section C (non-motor factors). These are sufficiently high, suggesting that the items of the checklist measure the same construct.





Executive function

Data analysis

Trails-Preschool test – Revised (adapted from Espy & Cwik 2004). The Trails-Preschool test – Revised (Trails-P) was developed as a downward extension of the Trail-Making Test (Reitan & Wolfson 1992) and provides a measure of inhibitory control and set switching. This measure uses a storybook format in which the child is presented with a ‘story book’ showing a family of dogs and the bones they are about to eat. The child is required to stamping on the stimuli according to different rules. The ‘control’ condition (1) for this task involves stamping the dog images according to size (smaller ones first, larger ones last). The ‘switch’ condition (2; attentional control) involves the alternative stamping of the dogs and then the bone images according to size. The ‘inhibit’ condition (3; response suppression) requires the child to ignore the previously salient dogs and stamp only their bone images according to size (smaller ones first, larger ones last). The ‘distraction’ condition (4), which includes cat stimuli now, still expects the child to stamp the dog and bones. The trials were timed using a stopwatch to the nearest 0.01 s. An efficiency score is computed for each task using a formula taking into account both accuracy and naming speed {[1/time)/square root (errors + 1)] × 100}.

Statistical analyses were implemented on SPSS v.22 (SPSS, Chicago, IL, USA). We first explored dependent variables to examine missing data points, normality of distributions (tested by Kolmogorov– Smirnov tests) and presence of outliers (defined by the Explore command of SPSS v.22). An alpha level of 0.05 was used for all statistical tests. A crosstab analysis of percentile scores for total performance on each assessment was conducted to determine the level of agreement between the assessments in order to classify children as at risk. To analyse between-group and gender differences in motor performance (children with DS and TD children), analyses of covariance (ANCOVAs) were conducted on the TGMD-2 locomotor and object control subtests raw scores as well as the MABC checklist scores, with group and sex as independent variable, and age and BMI percentiles as covariates. Partial correlations were calculated separately for children with DS and TD children to measure associations between the TRAILS-P, the TGMD-2 raw scores, and the MABC checklist, controlled for age and sex. Correlations were deemed significant if P < 0.05. To determine whether individuals with and without DS showed different correlations, Fisher’s z-score transformations and t-tests were applied using freeware (Preacher 2002).

Procedure Measurements were made in the gyms of the schools. The children had not attended any motor activity earlier and were dressed in sports gear/ apparel and running shoes or trainers. All safety measures with regard to the young participants’ physical activity were taken and external noise involving the distraction was minimised. Each child was assessed individually. In addition, there were meetings held with all school-children with the aim of familiarising with the examiner, and reduce anxiety during the examination, before the measurements. In order to ensure such outcome, the children did not know about the skills in advance. These skills were presented right before the examination. The role of the examiner was to assess the child in accordance with the instruction manual and guide correctly.

Results Motor assessment Test of gross motor development The TGMD-2 locomotor and object control subtest scores of the two groups are presented in Table 2. Significant differences were obtained between the DS group and the TD children on both TGMD-2 subtests. The children with DS scored significantly lower than the TD children with large effect sizes (ŋ2p > 0.50). Locomotion and object control scores were significantly correlated in the group of the TD children (r = 0.60) and the children with DS (r = 0.45). When gender differences were examined for the test scores, boys of the DS group were better performers of the locomotor and object control skill sum scores, whereas girls of the TD group were




F1,30 = 6.55, P = 0.016, η2p = 0.179 ns

more proficient at these scores. No significant differences were found for BMI.

ns ns

Movement Assessment Battery Children-2 checklist

BMI, body mass index; DS, Down’s syndrome; ns, not significant; TD, typically developing children.

ns ns 8–47 18–41 Locomotor skills Object control skills

27.2 ± 9.74 29.4 ± 6.30

41.8 ± 5.16 42.1 ± 2.47

28–48 37–45

F1,30 = 39.6, P < 0.001, η2p = 0.569 F1,30 = 80.3, P < 0.001, η2p = 0.728

ns ns

BMI Sex Age Group Min–Max Mean ± SD Min–Max Mean ± SD

TD DS

Table 2 Descriptive and inferential statistics of the Test of Gross Motor Development raw scores by group

Statistical analysis

Group × Sex


Group differences in the MABC checklist with analysis of covariance (ANCOVA) – controlled for age, gender and BMI percentile revealed that the DS group scored significantly more poorly on sections A (static/predictable) and B (dynamic/ unpredictable), and the TMS, but not on section C (non-motor factors; see Table 3). No main effects regarding age, gender or BMI percentiles were found for section A, B or the TMS score. A significant interaction was found for group × gender for section A, with boys (12.4 ± 5.75) of the DS group outperformed the girls (17.1 ± 5.64), whereas girls (0.57 ± 1.13) of the TD group were more proficient than the boys (1.55 ± 1.51) [Fgroup×gender(1,30) = 4.47, P = 0.043, ŋ2p = 0.130]. A tendency was found for age and section C with an increasing number of non-motor factors with increasing age [Fage(1,30) = 3.72, P = 0.063, ŋ2p = 0.110]. Large effect sizes after controlling for age, gender and BMI percentiles were found for section A (r = 0.86), section B (r = 0.84), and the TMS (r = 0.86), but not for section C (r = 0.13). The scores for sections A, B and C were significantly correlated in the group of the TD children (A & B: r = 0.74; A & C: r = 0.78; B & C: r = 0.51) and children with DS (A & B: r = 0.78; A & C: r = 0.48; B & C: r = 0.52) to a moderate to high degree. The TMS is interpreted using a traffic light system: class teachers and physical education teachers identified 17 (94.4%) children of the DS group as highly likely to have movement difficulty (red), and one (5.6%) as being at risk of movement difficulty (amber). In the group of TD children, two (11.1%) were classified as highly likely to have movement difficulties, two (11.1%) likely to face movement difficulties and 14 (77.8%) as having no movement difficulties (green).

Executive function Latencies as well as condition errors from each of the four TRAILS-P conditions were correlated, ranging in magnitude from 0.80 to 0.91, respec-





Table 3 Mean Movement Assessment Battery Children checklist subscores and standard deviations by group, controlled for age, gender and body mass index percentiles

DS

Section A (0–45) Section B (0–45) Section C (0–13) Total motor score (A + B) (0–90)

TD

Mean ± SD

Min–Max

Mean ± SD

Min–Max

Stat. analysis

14.2 ± 6.04 15.4 ± 5.79 5.28 ± 2.19 29.6 ± 11.2

2–25 4–26 1–9 8–51

1.17 ± 1.43 3.06 ± 2.18 4.67 ± 2.59 4.22 ± 3.37

0–12 0–8 0–9 0–12

Fgroup(1,30) = 98.0, P < 0.001, η2p = 0.766 Fgroup(1,30) = 73.3, P < 0.001, η2p = 0.710 ns Fgroup(1,30) = 96.4, P < 0.001, η2p = 0.763

DS, Down’s syndrome; ns, not significant; TD, typically developing children.

120,0

**

**

**

**

DS TD

TRAILS-P (s)

100,0 80,0 60,0 40,0 20,0 0,0

5,0 4,5

TRAILS-P (number of errors)

140,0

**

**

**

**

DS TD

4,0 3,5 3,0 2,5 2,0 1,5 1,0 0,5

A – Baseline B – Attentional C – Response D – Distraction suppression control control TRAILS-P - Condition

0,0

A – Baseline B – Attentional C – Response D – Distraction suppression control control TRAILS-P - Condition

Figure 1 Mean time and errors for conditions A, B, C and D as a function of experimental group (DS: Down syndrome; TD: typically developing children; whiskers represent standard deviation; ** P < 0.001).

tively, from 0.36 to 0.85. Latency and errors were correlated significantly within each condition (range 0.60–0.88). Group differences in the Trails-P with analysis of repeated measures with the covariates age, gender and BMI percentiles revealed that the DS group scored more poorly on all four conditions (latencies, errors, efficiency score) (see Figs 1,2). There were no main effects for condition, age or gender, but significant interactions of condition × group for latency [Fgroup×condition(3,96) = 5.64, P = 0.001, ŋ2p = 0.150], errors [Fgroup×condition(1.72,55.1) = 4.23, P = 0.024, ŋ2p = 0.117], and the efficacy score [Fgroup×condition(1.91,61.2) = 10.2, P < 0.001, ŋ2p = 0.241].

Relationship of Test of Gross Motor Development-2, Movement Assessment Battery Children-2 checklist and the Trail-Making Test for children Table 4 reports the partial correlations between the TGMD-subtest raw scores, the MABC checklist with the four different conditions of the TrailsPreschool Test controlled for the children’s age and sex. Correlations with medium to high effect sizes were obtained between all conditions of the Trails-P and sections A (static/predictable) and B (dynamic/ unpredictable) of the MABC checklist as well as for locomotor skills and object control skills in the group of children with DS. The TD group





TRAILS-P (efficiency score)

16,0 14,0

**

**

**

**

DS TD

12,0 10,0 8,0 6,0 4,0 2,0 0,0

A – Baseline B – Attentional C – Response D – Distraction suppression control control

TRAILS-P -Condition

Figure 2 Efficiency score for conditions A, B, C and D as a function of experimental group (DS: Down syndrome; TD: typically developing children; whiskers represent standard deviation; ** P < 0.001).

produced lower correlations on almost all relationships. No significant differences for correlations emerged between the TRAILS-P and the bottom-up assessment TGMD-2; however, comparisons of the baseline condition and attentional control of the TRAILS-P and the top-down assessment MABC-2 checklist revealed that they significantly differed from each other.

Discussion The aim of this study was to examine performancebased (bottom-up) and teacher-report (top-down) measures of children’s motor performance and EFs in school-age children with DS to investigate the relationship between these two performance domains. Regarding both domains separately, we could confirm the results of previous studies, which analysed motor skills (e.g. Hasan et al. 2012) and EF (e.g. Borella et al. 2013) in individuals with DS. The TD children achieved significantly better results in the locomotor and object control scores of the TGMD (cf. Table 2) and in sections A (static/predictable) and B (dynamic/unpredictable) of the MABC-2 checklist (cf. Table 3) compared to the children with DS. Referring to the MABC-2 checklist, the differences between both groups are particularly large on items, which require fine

motor skills, e.g. ‘fastens buttons’, dynamic balance/postural control, e.g. ‘hops on either foot’ or the ability to anticipate spatial-temporal interrelations, e.g. ‘hits/strikes a moving ball using a bat or racquet’ (Schott et al. 2014), which was reported before to be particularly difficult for individuals with DS (Horvat et al. 2013). The results also indicate that TD children show the greatest difficulties in performing such complex tasks. A similar picture has also been obtained for performing the four Trails-P conditions. The TD group achieved significantly better results in all conditions for mean time, errors and efficiency scores compared to the children with DS (cf. Figs 1,2). In comparison with the sample of Espy and Cwik (2004) of n = 103 TD children (45 boys, 58 girls, 3 age groups: 3-, 4- and 5-year-old children; mean age = 4.46, SD = 0.92 years), the children with DS in our study (with a comparable mental age; Carney et al. 2013) show considerably slower mean times on the Trails-P than the group of the 3-year olds, for all conditions. These strong developmental delays could be explained by the test procedure of the Trails-P, which requires the focus only on one cognitive ability in each condition, in addition to using capacity of the working memory by holding the rules in mind and working with it. This was shown to be difficult for children with DS (Lanfranchi et al. 2009; Costanzo et al. 2013) compared to MA-matched controls. No significant influence was shown for the BMI even though it was identified as potential factor of influence for motor performance (e.g. Okely et al. 2004) and EF (Reinert et al. 2013). Regarding the relationship between both domains, motor performance and EF correlated positively with medium to high effect sizes (cf. Table 4), but only for the group with DS (0.35 < r < 0.80). At the most complex task D (distraction), the children of the DS group with lower scores on locomotor skills and object control showed lower efficacy scores on the Trails-P and the strongest relationship (−0.54 < r < 0.80), both for the bottom-up and for the top-down approaches. On a neuroanatomical basis, Westendorp et al. (2011) explain the relationship between motor performance and EF with the role of the cerebellum, which is also suggested by Rigoli et al. (2012) and others (Koziol et al. 2011, 2014;


DS r TD r z DS r TD r z DS r TD r z DS r TD r z

A – baseline control

B – attentional control

C – response suppression

D – distraction

0.80** 0.50* 1.50

0.35 0.26 0.27

0.51 0.15 1.13

0.43 −0.16 1.70

0.60* 0.30 1.05

0.38 −0.03 1.18

0.61* 0.07 1.75

0.54* 0.02 1.60

Object control

0.79** 0.53* 1.32

0.54* 0.17 1.18

0.57* 0.18 1.28

0.38 −0.09 1.34

GMQ

Section B −0.64** 0.22 −2.69 −0.73** −0.01 −2.52 −0.40 −0.01 −1.13 −0.57* −0.17 −1.30

Section A −0.53* 0.50 −3.12 −0.56* 0.08 −1.95 −0.43 −0.03 −1.18 −0.69** −0.24 −1.65

−0.54* −0.39 −0.53

−0.43 −0.17 −0.79

−0.40 0.41 −2.35

−0.42 0.62* −3.21

Section C

MABC checklist (top-down assessment)


A z-obtained of 1.972244 would be statistically significant at P < 0.05. For all Trails-P scores applied, the higher the efficacy score, the better the performance. For the TGMD-2 scores applied, the higher the score, the better the performance; for all MABC-2 checklist scores applied, the lower the score, the better the performance. DS, Down’s syndrome; GMQ, Gross Motor Quotient; MABC-2, Movement Assessment Battery Children-2; TD, typically developing children; TGMD-2, Test of Gross Motor Development-2. * p < .05; ** p < .01.

Cognitive abilities

Locomotion

TGMD-2 (bottom-up assessment)

Motor skills

Table 4 Partial correlations (r) and differences in magnitude of correlations (Fisher’s z) across cognitive and motor indices for the sample of typically – developing control children (n = 18) and children with Down’s syndrome (n = 18) controlled for age and sex

868 volume 59 part 9 septemBer 2015






Koziol & Lutz 2013). Furthermore, the understanding of the development of large-scale brain networks, in which regions with cognitive and motor functions interact and communicate (e.g. PFC, basal ganglia, cerebellum), supports our results (Koziol & Lutz 2013). Carducci et al. (2013) analysed the morphological differences in different brain regions in children and adolescents with DS (n = 21) and an age-matched control sample (n = 27). Among other things, they found a grey matter volume reduction in the cerebellum, frontal lobes and the hippocampus, as well as a decrease of white matter volume in the left cerebellum, frontal and parietal lobes in individuals with DS compared with the control sample, whereas other regions showed volume preservation. These findings are in agreement with the review of Dierssen (2012) and help us understand why weak results of EF are associated with poorer results of motor skills and vice versa in children with DS. In addition, individuals with DS showed an abnormal sensorimotor integration or a compromised somatosensory system (Carvalho & Vasconcelos 2011), which seems to be important in generating EF (Koziol & Lutz 2013). Relationships found between EF and motor performance only for the children with DS in our study could be explained from several points of view. Both domains are intertwined sharing functional and structural mechanisms (Rigoli et al. 2012; Horvat et al. 2013). However, looking at the daily routine of TD children, more factors of influence have to be considered because there are children who achieve good results in EF without being physically active or good in sports, as well as children who show a high motor competence and weak results in school or EF. From the understanding that individual differences in EF are predominantly genetically determined (Friedman et al. 2008; Miyake & Friedman 2012), physical activity and the acquisition of motor skills could be only one option utilising the genetic capacity of EF. Although it is known that children with DS show interindividual different degrees of cognitive (Patterson et al. 2013) and motor (Volman et al. 2007) impairments, the possible performance range seems to be limited by their genetically based neurodevelopmental disorder compared with TD children. Furthermore, TD children have greater possibilities to gather movement experiences in a musical- or a sport-related context

improving both cognitive function and motor competence. This variety of options could lead to motor skill and EF independent profiles and thus explain the small correlation coefficients for the TD children. For example, Moreno et al. (2011) found an improvement of EF in TD children aged between 4 and 6 years applying short-term music training, whereas for individuals with DS, several barriers exist participating in physical activity (Barr & Shields 2011). However, it is known that motor competency only develops as a result of practice, which means extensive participation in a variety of physical activities. Following this idea, the largest relationship between motor competence and distraction is probably due to the fact that children with DS have generalised difficulties in suppressing irrelevant or no longer relevant information (Borella et al. 2013), which is necessary in condition D of the Trails-P. From a methodical point of view, the medium to high significant correlations (cf. Table 4) between bottom-up assessment, top–down assessment and EF for the DS sample supports the suggestion of Kennedy et al. (2013) using a combination of both approaches to assess motor performance also in the context of cognitive abilities for getting a more comprehensive picture of the individuals profile. Using the Trails-P for both groups is, on the one hand, a strength because the same tests allow a direct comparison of the results, which seems important regarding the difficulties in testing and defining the construct EF (Wasserman & Wasserman 2013). On the other hand, this could be classified as a limitation because the Trails-P was too easy for some of the TD children, which is a possible explanation for the weaker relationships of the TD children. An important limitation is the inclusion of only a group of TD children, but not a group of MA-matched children (Burack et al. 2002; Silverman 2007). We have not included a comparison group based upon MA, which would allow eliminating the expected delays in development due to the group with lower cognitive functioning because motor skills can only be developed with adequate training over several years. However, matching on MA typically results in group comparisons with significantly different chronological age, which means different biological maturation and life experiences that can influence task performance (Burack et al. 2002). Although the





sample size of our study is similar to previous studies (Lanfranchi et al. 2010; Borella et al. 2013), the number of participants limits the overall generalisability, in particular further classifications like differences between boys and girls in each group. Therefore, a bigger sample size would lead to general and more meaningful results. This appears particularly important for special populations like individuals with DS, who show different degrees of motor (Volman et al. 2007) and cognitive impairments (Patterson et al. 2013). The crosssectional design of this study could be evaluated as an adequate approach providing first data about the relationship between performance-based, teacherreport measures of motor performance and EF in children with DS. However, the cross-sectional design also warrants that the results have to be interpreted with caution. On basis of our results and the relationship between motor competence and EF, both on a structural and on a functional level, a reciprocal relationship could be suggested. Hence, it would be interesting to investigate as to what extent the improvement of motor competence could positively influence EF and vice versa, both in children with DS and in TD children. Horvat et al. (2013) conclude in their recent study that individuals with DS are trainable and have a vast potential improving their motor performance, which supports our understanding. Concerning cognitive functions, at the moment, it is not clear which activities lead to the most improvements in EF (Diamond 2013). The identification of a causal relationship appears very important to ensure feasibility of practical implementation. This could provide aids for decision-making for teachers and therapists in decision guidance to create lessons and therapy adequate to the target group. In order to achieve this aim, studies with a longitudinal design and the application of statistical methods like structural equation modelling are needed to clarify speculations about the cause-and-effect relationships. In conclusion, the findings from this study confirm that children with DS are not only impaired in higher-order EF, but showing also deficits in motor skills (Horvat et al. 2013). The presented results stress the importance of early interventions facilitating cognitive abilities and motor skills, ideally combined.

Acknowledgements We are very grateful to the teachers, parents and children who were willing to participate in this study. We also thank Orania Moussoli for her assistance with data collection and data entry.

Conflict of interest The authors declare that there is no confict of interest.

References Barr M. & Shields N. (2011) Identifying the barriers and facilitators to participation in physical activity for children with Down syndrome. Journal of Intellectual Disability Research 55, 1020–33. Best J. R. & Miller P. H. (2010) A developmental perspective on executive function. Child Development 81, 1641– 60. Borella E., Carretti B. & Lanfranchi S. (2013) Inhibitory mechanisms in Down syndrome: is there a specific or general deficit? Research in Developmental Disabilities 34, 65–71. Brown T. (2012) Are performance-based and self-report measures of children’s motor skill abilities linked? Occupational Therapy in Health Care 26, 283–305. Burack J. A., Iarocci G., Bowler D. & Mottron L. (2002) Benefits and pitfalls in the merging of disciplines: the example of developmental psychopathology and the study of persons with autism. Development and Psychopathology 14, 225–37. de Campos A. C., Savelsbergh G. J. & Rocha N. A. (2012) What do we know about the atypical development of exploratory actions during infancy? Research in Developmental Disabilities 33, 2228–35. Capio C. M. & Rotor E. R. (2010) Fundamental movement skills among Filipino children with Down syndrome. Journal of Exercise Science & Fitness 8, 17–24. Carducci F., Onorati P., Condoluci C., Di Gennaro G., Quarato P. P., Pierallini A. et al. (2013) Whole-brain voxel-based morphometry study of children and adolescents with Down syndrome. Functional Neurology 28, 19–28. Carney D. P., Brown J. H. & Henry L. A. (2013) Executive function in Williams and Down syndromes. Research in Developmental Disabilities 34, 46–55. Carvalho R. L. & Vasconcelos D. A. (2011) Motor behavior in Down syndrome: atypical sensorimotor control.





In: Prenatal Diagnosis and Screening for Down Syndrome (ed. S. Dey), pp. 34–42. In Tech Publishers, Rijeka, Croatia. Connolly B. H. & Michael B. T. (1986) Performance of retarded children, with and without Down’s syndrome, on the Bruininks Oseretsky test of motor proficiency. Physical Therapy 66, 344–8. Costanzo F., Varuzza C., Menghini D., Addona F., Gianesini T. & Vicari S. (2013) Executive functions in intellectual disabilities: a comparison between Williams syndrome and Down syndrome. Research in Developmental Disabilities 34, 1770–80. Diamond A. (2000) Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child Development 71, 44–56. Diamond A. (2013) Executive functions. Annual Review of Psychology 64, 135–68. Dierssen M. (2012) Down syndrome: the brain in trisomic mode. Nature Reviews. Neuroscience 13, 844–58. Espy K. & Cwik M. (2004) The development of a Trail Making Test in young children: the TRAILS-P. The Clinical Neuropsychologist 18, 1–12. Evaggelinou C., Tsigilis N. & Papa A. (2002) Construct validity of the Test of Gross Motor Development: A cross-validation approach. Adapted Physical Activity Quarterly 19, 483–95. Friedman N. P., Miyake A., Young S. E., Defries J. C., Corley R. P. & Hewitt J. K. (2008) Individual differences in executive functions are almost entirely genetic origin. Journal of Experimental Psychology. General 137, 201–25. van Gameren-Oosterom H. B. M., van Dommelen P., Schönbeck Y., Oudesluys-Murphy H. M., van Wouwe J. P. & Buitendijk S. E. (2012) Prevalence of overweight in Dutch children with Down syndrome. Pediatrics 130, e1520–6. van Gameren-Oosterom H. B. M., Fekkes M., Reijneveld S. A., Oudesluys-Murphy A. M., Verkerk P. H., van Wouwe J. P. et al. (2013) Practical and social skills of 16–19-year-olds with Down syndrome: independence still far away. Research in Developmental Disabilities 34, 4599–607. de Graaf G., Vis J. C., Haveman M., van Hove G., de Graaf E. A. B., Tijssen J. G. P. et al. (2011) Assessment of prevalence of persons with down syndrome: a theorybased demographic model. Journal of Applied Research in Intellectual Disabilities 24, 247–62.

sented at Humanities, Science and Engineering Research (SHUSER), 2012 IEEE Symposium, Kuala Lumpur. 217–21. doi: 10.1109/SHUSER.2012.6268854. Henderson S., Sugden D. & Barnett A. (2007) Movement Assessment Battery for Children, 2nd edn. Pearson, Oxford. Hickey F., Hickey E. & Summar K. L. (2012) Medical update for children with Down syndrome for the pediatrician and family practitioner. Advances in Pediatrics 59, 137–57. Horvat M., Croce R., Tomporowski P. & Barna M. C. (2013) The influence of dual-task conditions on movement in young adults with and without Down syndrome. Research in Developmental Disabilities 34, 3517– 25. Jobling A. (1998) Motor development in school-aged children with Down syndrome: a longitudinal perspective. International Journal of Disability, Development and Education 45, 283–93. Kennedy J., Brown T. & Stagnitti K. (2013) Top-down and bottom-up approaches to motor skill assessment of children: are child-report and parent-report perceptions predictive of children’s performance-based assessment results? Scandinavian Journal of Occupational Therapy 20, 45–53. Kent R. D. & Vorperian H. K. (2013) Speech impairment in Down syndrome: a review. Journal of Speech, Language, and Hearing Research 56, 178–210. Kourtessis T., Tsigilis N., Tzetzis G., Kapsalas T., Tserkezoglou S. & Kioumourtzoglou E. (2003) Reliability of the Movement Assessment Battery for Children Checklist in Greek school environment. European Journal of Physical Education 8, 202–10. Koziol L. F. & Lutz J. T. (2013) From movement to thought: the development of executive function. Applied Neuropsychology: Child 2, 104–15. Koziol L. F., Budding D. E. & Chidekel D. (2011) From movement to thought: executive function, embodied cognition, and the cerebellum. Cerebellum (London, England) 11, 505–25. Koziol L. F., Budding D., Andersen N., D’Arrigo S., Bulgheroni S., Imamizu H. et al. (2014) Consensus paper: the cerebellum’s role in movement and cognition. Cerebellum (London, England) 13, 151–77. Lanfranchi S., Jerman O. & Vianello R. (2009) Working memory and cognitive skills in individuals with Down syndrome. Child Neuropsychology 15, 397–416.

Hartman E., Houwen S., Scherder E. & Visscher C. (2010) On the relationship between motor performance and executive functioning in children with intellectual disabilities. Journal of Intellectual Disability Research 54, 468–77.

Lanfranchi S., Jerman O., Dal Pont E., Alberti A. & Vianello R. (2010) Executive function in adolescents with Down syndrome. Journal of Intellectual Disability Research 54, 308–19.

Hasan H. B., Abdullah N. M. & Suun A. (2012) The assessment of gross motor skills development among down syndrome children in Klang Valley. Paper pre-

Loane M., Morris J. K., Addor M.-C., Arriola L., Budd J. & Doray B. (2013) Twenty-year trends in the prevalence of Down syndrome and other trisomies in Europe:





impact of maternal age and prenatal screening. European Journal of Human Genetics 21, 27–33. Lott I. T. & Dierssen M. (2010) Cognitive deficits and associated neurological complications in individuals with Down’s syndrome. The Lancet Neurology 9, 623–33. Miyake A. & Friedman N. P. (2012) The nature and organization of individual differences in executive functions: four general conclusions. Current Directions in Psychological Science 21, 8–14. Moreno S., Bialystok E., Barac R., Schellenberg E. G., Cepeda N. J. & Chau T. (2011) Short-term music training enhances verbal intelligence and executive function. Psychological Science 22, 1425–33. Okely A. D., Booth M. L. & Chey T. (2004) Relationships between body composition and fundamental movement skills among children and adolescents. Research Quarterly for Exercise and Sport 75, 238–47. Palisano R. J., Walter S. D., Russell D. J., Rosenbaum P. L., Gémus M., Galuppi B. E. et al. (2001) Gross motor function in children with Down syndrome: creation of motor growth curves. Archives of Physical Medicine and Rehabilitation 82, 494–500. Patterson T., Rapsey C. M. & Glue P. (2013) Systematic review of cognitive development across childhood in Down Syndrome: implications for treatment interventions. Journal of Intellectual Disability Research 57, 306– 18. Piek J. P., Dyck M. J., Nieman A., Anderson M., Hay D., Smith L. M. et al. (2004) The relationship between motor coordination, executive functioning and attention in school aged children. Archives of Clinical Neuropsychology 19, 1063–76. Pitetti K., Baynard T. & Agiovlasitis S. (2013) Children and adolescents with Down syndrome, physical fitness and physical activity. Journal of Sport and Health Science 2, 47–57. Preacher K. J. (2002) Calculation for the test of the difference between two independent correlation coefficients [computer software]. Available at: http://quantpsy.org (retrieved 28 December 2013). Presson A. P., Partyka G., Jensen K. M., Devine O. J., Rasmussen S. A., McCabe L. L. et al. (2013) Current estimate of Down syndrome population prevalence in the United States. Journal of Pediatrics 163, 1163–8. Reinert K. R. S., Po’e E. K. & Barlin S. L. (2013) The relationship between executive function and obesity in children and adolescents: a systematic literature review. Journal of Obesity. doi: 10.1155/2013/820956. Reitan R. & Wolfson D. (1992) Neuropsychological Evaluation of Older Children. Manual. Neuropsychology Press, Tucson, AZ.

Rigoli D., Piek J. P., Kane R. & Oosterlaan J. (2012) An examination of the relationship between motor coordination and executive functions in adolescents. Developmental Medicine & Child Neurology 54, 1025–31. Rowe J., Lavender A. & Turk V. (2006) Cognitive executive function in Down’s syndrome. British Journal of Clinical Psychology 45, 5–17. Schott N., Holfelder B. & Mousouli O. (2014) Motor skill assessment in children with Down syndrome: relationship between performance-based and teacher-report measures. Research in Developmental Disabilities 35, 3299–312. Silverman W. (2007) Down syndrome: cognitive phenotype. Mental Retardation and Developmental Disabilities Research Reviews 13, 228–36. Simons J., Daly D., Theodorou F., Caron C., Simons J. & Andoniadou E. (2008) Validity and reliability of the TGMD-2 in 7–10-year-old Flemish children with intellectual disability. Adapted Physical Activity Quarterly 25, 71–92. Ulrich D. A. (2000) Test of Gross Motor Development Examiner’s Manual, 2nd edn. PRO-ED, Austin, TX. Volman M. J., Visser J. J. & Lensvelt-Mulders G. J. (2007) Functional status in 5- to 7-year-old children with Down syndrome in relation to motor ability and performance mental ability. Disability and Rehabilitation 29, 25–31. Wassenberg R., Feron F. J. M., Kessels A. G. H., Hendriksen J. G. M., Kalff A. C. & Kroes M. (2005) Relation between cognitive and motor performance in 5to 6-year-old children: results from a large-scale crosssectional study. Child Development 76, 1092–103. Wasserman T. & Wasserman L. D. (2013) Toward an integrated model of executive functioning in children. Applied Neuropsychology: Child 2, 88–96. Westendorp M., Hartman E., Houwen S., Smith J. & Visscher C. (2011) The relationship between gross motor skills and academic achievement in children with learning disabilities. Research in Developmental Disabilities 32, 2773–9. Wu J. & Morris J. K. (2013) The population prevalence of Down’s syndrome in England and Wales in 2011. European Journal of Human Genetics 21, 1016–19. Zigman W. B. & Lott I. T. (2007) Alzheimer’s disease in Down syndrome: neurobiology and risk. Mental Retardation and Developmental Disabilities Research Reviews 13, 237–46.

Accepted 21 January 2015


Motor skill assessment in children with Down Syndrome: relationship between performance-based and teacher-report measures.

[Relationship between Intelligence and Executive Function].

Relationship between acquisition of motor function and vestibular function in children with bilateral severe hearing loss.

Disentangling the relationship between children's motor ability, executive function and academic achievement.

The Relationship Between Gait, Gross Motor Function, and Parental Perceived Outcome in Children With Clubfeet.

Relationship between Neural Activity and Executive Function: An NIRS Study.

Do Perceptions of Competence Mediate The Relationship Between Fundamental Motor Skill Proficiency and Physical Activity Levels of Children in Kindergarten?

Motor skill learning between selection and execution.

executive function in patients with clinically isolated syndrome.

Relationship between lung function and metabolic syndrome.

Improving the motor skill of children with posterior fossa syndrome: a case series.

Theory of mind and emotional functioning in fibromyalgia syndrome: an investigation of the relationship between social cognition and executive function.

The Role of Executive Functions in Social Cognition among Children with Down Syndrome: Relationship Patterns.

The link between impaired theory of mind and executive function in children with cerebral palsy.

Examination of motor skill competency in students: evidence-based physical education curriculum.

Relationship between leptin and lung function in young healthy children.

Relationship between cognitive dysfunction, gait, and motor impairment in children and adolescents with neurofibromatosis type 1.

Relations between fine motor skill and parental report of attention in young children with neurofibromatosis type 1.

Relationship between dressing and motor function in stroke patients: a study with partial correlation analysis.

Relationship between Insulin-Resistance Processing Speed and Specific Executive Function Profiles in Neurologically Intact Older Adults.

The mediating role of metacognition in the relationship between executive function and self-regulated learning.

Executive Function in Previously Institutionalized Children.

Executive function in children with prenatal cocaine exposure (12-15years).

Relationship between WISC verbal-performance discrepancies and motor and psychomotor abilities of children with learning disabilities.