Research in Developmental Disabilities 35 (2014) 3299–3312

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Research in Developmental Disabilities

Motor skill assessment in children with Down Syndrome: Relationship between performance-based and teacher-report measures Nadja Schott *, Benjamin Holfelder, Orania Mousouli University of Stuttgart, Department of Sport and Exercise Science, Allmandring 28, 70569 Stuttgart, Germany

A R T I C L E I N F O

A B S T R A C T

Article history: Received 12 April 2014 Received in revised form 4 August 2014 Accepted 4 August 2014 Available online

Results: of previous studies show a large interindividual variability with regard to motor skills and motor abilities in children with Down Syndrome (DS). In order to provide detailed information for intervention, adequate assessment methods seem to be necessary to address the child’s unique motor profile. Typically, children are either examined using a bottom-up (performance-based assessment of motor skills) or a top-down approach (e.g. client-report measure), but rarely both approaches. The aim of this study was to examine the relationship between standardized performance-based, and teacher-report measures of children’s motor performance. The performance- and process-based assessment Test of Gross Motor Development (TGMD-2), and the teacher-based Movement Assessment Battery – Checklist (MABC-C) for young children were used to assess the motor performance of 18 children with DS (11 boys, 7 girls) aged 7–11 years (M = 9.06, SD = 0.96) and an age- and sex-matched sample of typically developing (TD) 18 children (11 boys, 7 girls; M = 8.99, SD = 0.93). TD children achieve consistently better results compared to children with DS, both in the TGMD-2 and MABC-C, which differ significantly in most cases. When gender differences were examined for the TGMD-2 scores, boys with DS were better performers of the run, gallop, leap, and catch, as well as the locomotor and objectcontrol skill sum scores, whereas girls of the TD group were more proficient in these areas. TD children achieve significantly better results in 21 out of 28 items of Section A + B of the MABC-C, compared to the children with DS; whereas there are no significant differences for Section C (non-motor factors). Our results show more significant relationships between TGMD-2 and MABC-C sub- and overall scores for the TD sample compared to the children with DS. The correlations range between r = .21 and .65 for TD children and between r = .15 and .65 for the children with DS. The correlations between both approaches show that the combination of both methods could be useful in getting a more detailed picture of the child’s individual motor profile in order to create tailor-made therapies and interventions, both for children with DS and TD children. ß 2014 Elsevier Ltd. All rights reserved.

Keywords: Down Syndrome Motor skill performance TGMD-2 MABC Checklist

* Corresponding author. Tel.: +49 711 68563042; fax: +49 711 68563165. E-mail addresses: [email protected] (N. Schott), [email protected] (B. Holfelder), [email protected] (O. Mousouli). http://dx.doi.org/10.1016/j.ridd.2014.08.001 0891-4222/ß 2014 Elsevier Ltd. All rights reserved.

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1. Introduction Various studies confirm that children with Down Syndrome (DS), a genetically based neurodevelopmental disorder, show a delayed motor and mental development (Jobling, 1998; Patterson, Rapsey, & Glue, 2013; Volman, Visser, & LensveltMulders, 2007). Moreover, individuals with DS often do not achieve the recommended level of physical activity (PA) (Barr & Shields, 2011) and, typically, show low fitness levels (Sayers Menear, 2007). It can be suggested that these factors result in the fact that children with DS achieve lower scores in gross and fine motor skills (Connolly & Michael, 1986; Hasan, Abdullah, & Suun, 2012). Additionally, motor abilities like coordination, balance and strength (Capio & Rotor, 2010) may not be as developed as the ones peers without DS would show. Gross motor skills include fundamental movement skills (FMS) like throwing, catching and kicking. FMS are the building blocks for sport specific skills (Robinson & Goodway, 2009). In order to participate in organized sport activities children and adolescents (with and without DS) need to be able to master FMS (Barr & Shields, 2011; Hardy, King, Farrell, Macniven, & Howlett, 2010; Hasan et al., 2012; Holfelder & Schott, 2014). Physical activity in an organized form not only causes increased social interaction with peers and the development of FMS as two important factors of being active (Barr & Shields, 2011; Capio & Rotor, 2010), but may also result in psychological and physiological benefits (Sanyer, 2006). Results of previous studies show a large interindividual variability with regard to motor skills and motor abilities in children with DS (Dolva, Coster, & Lilja, 2004; Volman et al., 2007). In order to provide detailed information for intervention strategies to support the everyday lives of children with DS, adequate assessment methods seem to be necessary to address the child’s unique motor profile (Davis, 2008; Kennedy, Brown, & Chien, 2012). In the motor skill assessment, a distinction between bottom-up and top-down approaches could be made (Brown, 2012). The bottom-up approach could be characterized as a performance-based assessment of motor skills with the help of a standardized and norm-referenced test battery (Kennedy et al., 2012), like the Test of Gross Motor Development (TGMD-2; Ulrich, 2000). Cools, De Martelaer, Samaey, and Andries (2009) report on disadvantages of this approach: the complex administration and scoring with a poor relevance of the test items have little relevance for everyday life. The client-report measure, as an example of 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; Kennedy et al., 2012). An example of this method is a questionnaire completed by the child, the family or the caregivers (Kennedy et al., 2012), such as the Movement Assessment Battery – Checklist (MABC-C; Henderson, Sugden, & Barnett, 2007). Kennedy, Brown, and Stagnitti (2013) encourage therapists to use a combination of both approaches to evaluate the motor skill performance of children. This view is supported by Davis (2008), because children with DS show different types of motor problems – a simple qualitative assessment of fine and gross motor skills would be insufficient in this case. Kennedy et al. (2012), for example, examined whether there is an association between performance-based, child-report and parentreport measures of motor skills in 38 (25 males, 13 females) TD children, between 8 and 12 years old. Assessing the motor skills performance of these children, they applied the Bruininks-Oseretsky Test of Motor Proficiency-Second Edition (BOT-2; Bruininks & Bruininks, 2005). In addition, the MABC-2 (checklist components only; Henderson et al., 2007) was used to assess the children’s motor performances in everyday life from a parent’s perspective. They reported significant moderate correlations (rho = .37–.54) for all 38 children between BOT-2 and MABC-2 Checklist scores for all composites, except the Fine Manual Control composite scores. These results highlight the need to consider the parents’ perspectives in assessing children’s motor skills in everyday life (Kennedy et al., 2012). From the methodological perspective, this seems particularly important in young children, because self-reported outcomes are not valid and reliable before the age of nine (Arbuckle & Abetz-Webb, 2013). Furthermore, the delayed mental development and the cognitive impairments of children with DS (Costanzo et al., 2013; Volman et al., 2007) might lead to difficulties in taking part in self-report measures. As far as we know, no study with a combination of performance-based and teacher-report measures of motor skills in children with DS has been conducted. In general, there are not that many studies which examined motor skills in children with DS; sometimes only subdimensions have been assessed (Gupta, Rao, & Kumaran, 2011; Wang, Long, & Liu, 2012). Table 1 provides an extensive overview of previous studies adressing motor skills in children with DS. The purpose of this study was to examine the relationship between performance-based (bottom-up) and teacher-report (top-down) measures of motor skills in children with DS and TD peers. This is achieved by analyzing the results of TD children and children with DS for (1) performing the TGMD-2, (2) the MABC-C scores given by the teacher and (3) the relationship between MABC-C scores and the sub dimensions ‘‘locomotion’’, ‘‘object-control’’ scores as well as the gross motor quotient (GMQ) of the TGMD-2.

2. Methods 2.1. Sample 36 children (DS = 18, TD = 18) between the ages of 7 and 11 were included in the study. The participants were matched by 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

Table 1 Studies on motor performance in children with Down Syndrome. Characteristics of study sample

Study design

Instruments

Main results for motor performance

Limitations mentioned by the authors

Connolly and Michael (1986) USA

DS: n = 12, ø 9.16 y (< n = 3, , n = 9) CG: mentally retarded n = 12, ø 9.25 y (< n = 7, , n = 5)

Cross-sectional

Bruininks Oseretsky Test of Motor Proficiency (BOTMP)

CG scored significantly higher compared to DS for running speed (p < .005), gross motor skill composite (p < .05), balance (p < .05) visual motor skill control (p < .05) and fine motor skill composite (p < .05) of the BOTMP; no sex differences within the groups; females with DS scored significant lower compared to females of the CG for running speed, visual motor ability, strength, speed, dexterity and fine motor composite scores.

Small sample size, no attempt to delineate possible causes of differences between the DS and CG (mentally retarded).

Jobling (1998) Australia

DS: n = 99 99 (< n = 54, , n = 45) age range: 10–17 y; 205 four age groups AG1: n = 53, ø 10.55 y (< n = 31, , n = 22) AG2: n = 63, ø 12.56 y (< n = 35, , n = 28) AG3: n = 38, ø 14.51 y (< n = 22, , n = 16) AG4: n = 51, ø 16.53 y (< n = 31, , n = 20)

Longitudinal

Bruininks Oseretsky Test of Motor Proficiency (BOTMP) Stanford-Binet Intelligence Scale (L-M)

Cluster analysis identified two distinct profiles: (1) high No limitations are scores in the running speed and agility subtest (more mentioned by the boys) and (2) high scores in the visual-motor subtest authors. (more girls); balance subtest scores were low in both clusters; most children stayed in the same cluster across the age groupings; all children had difficulties with items which require precise movements of limbs, even at the age of 16; items requiring specific muscle strength were difficult for most children; the performance in items like running speed and agility and visual-motor control were at their chronological age level; lower limp pathology was considered as a limiting factor in motor proficiency

Jobling (1999) Australia

DS: n = 99 (< n = 54, , n = 45) age range: 10–17 y; 205 four age groups AG1: n = 53, ø 10.55 y (< n = 31, , n = 22) AG2: n = 63, ø 12.56 y (< n = 35, , n = 28) AG3: n = 38, ø 14.51 y (< n = 22, , n = 16) AG4: n = 51, ø 16.53 y (< n = 31, , n = 20)

Cross-sectional part-longitudinal

Bruininks Oseretsky Test of Motor Proficiency (BOTMP) Stanford-Binet Intelligence Scale (L-M)

Cross-sectional results: Significant age effect for all No limitations are subject point scores F(3,200) = 16.02, p < .001; follow- mentioned by the up ANOVA showed a significant age effect for each authors. subtest; age 10 compared with age 12 significant bilateral coordination F(1,114) = 9.88, p < .005, upper limb coordination F(1,114) = 12.57, p < .001, upper limb speed F(1,113) = 14.89, p < .001. dexterity F(1,114) = 13.17, p < .001; Longitudinal results: Cluster analysis of all BOTMP assessments 263 (< 145, , 118) revealed 2 clusters with significant differences regarding age-equivalent scores for running speed and agility F(1,259) = 358.4 p < .001, balance F(1,259) = 41.91, p < .001, visual-motor control F(1,114) = 64.48, p < .001; the first cluster with significantly more girls (X2 = 17.69, p < .001), had a higher score for running speed and agility and a lower score for balance and visual-motor control.

Spano` et al. (1999) Italy

DS: n = 22 (< n = 13, , n = 9) aged between 4.5 and 14 y

Cross-sectional

Movement Assessment Battery for Children (Movement ABC) Developmental Test of Visual-Motor Integration

Overall, the children scored below the 5th percentile for their age in both tests; in some gross motor skills a delayed development but regular acquisitions have been observed; in fine motor skills stronger impairments and a smaller development with age could be identified; balance and ball skills showed a greater variability, whereas tasks which require bimanual coordination were most impaired.

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Authors/Country

Cross-sectional design; some children had received regular interventions before the study; small number of motor tasks were used. 3301

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Table 1 (Continued ) Characteristics of study sample

Study design

Instruments

Main results for motor performance

Palisano et al. (2001) Canada

DS: n = 121 (< n = 65, , n = 56) ø 2.41  1.73 years (range between 0.14 and 6 y)

Cross-sectional

Gross Motor Function Measure (GMFM)

Both groups (G1: mild (n = 51) and G2: Moderate/severe No limitations are mentioned by the (n = 70) motor impairment) show the largest change authors. during infancy; G1: Pseudo R2 = .848; G2: Pseudo R2 = .818; children of G1 have approximately 25% faster improvement in GMFM scores compared to children of G2; overall, on average; children with DS do not achieve all gross motor functions by the age of 6.

Passarini (2001) USA

DS: n = 26 G1: n = 13 (< n = 8, , n = 5) ø 7.75 years (range between 6 and 10 y) G2: n = 13 (< n = 6, , n = 7), ø 8.75 (range between 6 and 10 y)

Longitudinal (G1: 12 weeks intervention, 3 sessions/week with at least 30 min/session; G2: Handwriting without tears program)

Test of Gross Motor Skills Development (TGMD)

The TGMD total score of G1 significantly (p < .01) improved during 12 weeks intervention; G2 did not improve significantly (p = .55) in TGMD total scores during the 12 weeks; G1 showed no significant difference (p = .51) between posttest (after 12 weeks intervention) and 2nd posttest (2 weeks after the intervention was finished).

No limitations are mentioned by the author.

Volman et al. (2007) The Netherlands

DS: n = 25, ø 6.83 y (< n = 13, , n = 12)

Cross-sectional

Movement Assessment Battery for Children (MABC) Pediatric Evaluation Disability Inventory (PEDI) Gross-Form Board (GFB)

Results of the M-ABC (high score = poor performance): manual dexterity: 10.1  3.9 (=67%); ball skills: 3.1  2.7 (=31%); balance: 6.1  4.4 (=41%); Motor ability is a strong predictor (.96) of the functional status, compared to the performance mental ability (.17); Functional status explained 70% of the variance in the model.

Small sample size; cross-sectional design; not possible to make valid conclusions about causality.

Capio and Rotor (2010) DS: n = 33, ø 7.06  2.50 y (< n = 13, , n = 12) Cross-sectional Philipines AG1 (3–5 y): n = 10 AG2 (6–8 y): n = 12 AG3 (9–11 y): n = 11

Standardized checklists for FMS: (1) overhand throwing; (2) catching; (3) standing long jump; (4) kicking and (5) running

Significant age differences for most of the skill components in all 5 assessed skills: except for leg-foot preparation (p = .076) and action (p = .929) in kicking, arm action in throwing (p = 0.078), arm preparation in catching (p = .07) and arm preparation in standing long jump (p = .103); reasons for the non-significant differences were related to coordination and balance deficits and weakness of the legs and the trunk.

Descriptive study design; applied instruments (not criterion-referenced); no between-subject design.

Gupta et al. (2011) India

Balance subscale of Bruininks Oseretsky Test of Motor Proficiency (BOTMP) Handheld dynamometer to measure the lower limb muscle strength

In the IG, the lower limb strength of all measured muscle groups increased significantly compared to the CG (p = .001–.03); the IG showed a significant improvement in 5 of 8 balance subscales (p = .001–.016) and for the total score of the balance subscale of the BOTMP compared to the CG (p = .007); specific exercise training program may improve the strength and balance.

Small sample size; no blinding ! assessor knew the attribution of the patients to the group; no attention and intervention was given to the CG.

DS: N = 23 (IG: n = 12: ø 13.50 y, < n = 8, , n = 4; CG: n = 11: ø 13.00 y, < n = 6, , n = 5)

Longitudinal (randomized controlled trial); Intervention: 6 weeks, 3 times/week

Limitations mentioned by the authors

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Authors/Country

DS: n = 30 (< n = 16, , n = 14); age range from 3 to 10 years

Cross-sectional

Test of Gross Motor Skills Development (TGMD-2)

Only 10% score above average and 30% achieve average No limitations are scores; 60% are below average of whom 36.67% score mentioned by the poor (20%) and very poor (16,67%); no significant sex authors. differences for locomotor (p = .70) and object control (p = .96) skills; significant relationship (r = .608, p < .001) between locomotor and object control skills for all n = 30 children.

Tiernan (2012) USA

DS: n = 20, ø 7.94  1.25 y (< n = 16, , n = 4) CG (TD): n = 20, ø 7.94  1.57 y (< n = 16, , n = 4)

Cross-sectional

Test of Gross Motor Skills Development (TGMD-2)

Locomotor raw score: DS 21.16  11.88, TD 44.95  3.02, t(37) = 8.67, p < .001; object control raw score: DS 24.80  12.30, TD 42.85  4.00, t(38) = 6.24, p < .001; 40-ft timed run (s): DS 5.13  1.13, TD 3.10  0.28 t(37) = 7.77, p < .001; children with DS scored significantly lower than children with TD on all items of the TGMD-2; significant differences for all assessed range of motion degrees and leg strength between DS and TD children were observed.

Wang et al. (2012) Taiwan

DS: n = 23, ø 14.4  2.8 y (< n = 16, , n = 7) CG (TD): n = 18, ø 13.8  3.6 y (< n = 11, , n = 7)

Cross-sectional

2 dimensions of the Gross Motor Function Measure (GMFM) 4 subtests of the Bruininks Oseretsky Test of Motor Proficiency (BOT-2) Kistler force plate for measurement of the postural control (COP center of pressure)

GMFM: n = 19 with DS did not achieve the full score on No limitations are the standing dimension; n = 21 with DS did not get full mentioned by the scores on the walk/run/jump dimensions; BOT-2 (range authors. 1–35; ø 15 points): Bilateral coordination 5.65  2.67, balance 4.48  1.08. Run speed/agility 5.26  2.91 and strength 6.13  3.17 for DS group; standing dimension and strength subtest are significant predictors (86.0%) of COPx (medial/lateral direction in cm); standing dimension, walk/run/jump and strength subtest are significant predictors (85.9%) for COPy (anterior/posterior direction in cm); strength subtest is a significant predictor (83.5%) for COPv (cm/s).

Note: AG, age group; CG, control group; DS, down syndrome; G, group; IG, intervention group; TD, typically developing.

Sample size; children of CG were not randomly selected ! may aboveaverage be interested in sports and fitness; no cognitive assessment; Actiheart device was not validated for children with DS.

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Hasan et al. (2012) Malaysia

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Table 2 Demographics and physical characteristics (M  SD).

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

DS

TD

Stat. 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

p > .05 p > .05 p > .05 p > .05 p > .05 p > .05

recruited through a primary school from the same area. Exclusion criteria (for both groups) included major health conditions. There are no significant differences with regard to the BMI. Using overweight and obesity definitions based on BMI,1 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%). 22.7% of the boys were obese and 31.8% were overweight. 28.6% of the girls were obese and 7.1% were overweight. There were no significant differences between the groups on any of these variables. Only one child in the DS group reported being physically active, whereas 10 children in the TD group said they are physically active (CHI2(4) = 14.2, p = .007). Table 2 demonstrates the sample’s characteristics. Informed written consent was obtained from organizations and parents prior to the beginning of testing, and participants themselves were also told that they could opt out at any time. All procedures were in accordance with ethical standards of the Declaration of Helsinki, legal requirements and international norms. 2.2. Materials 2.2.1. Test of Gross Motor Development (TGMD-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 norm-referenced test designed to assess gross motor functioning of children between 3 and 10 years of age (Ulrich, 2000). This test measures 12 gross motor skills that are usually acquired by children in preschool and early elementary grades. They are subdivided in two skill areas: locomotor (LM; running, galloping, hopping, leaping, horizontal jumping, and sliding) and object control (OC; striking, bouncing, catching, kicking, throwing, and rolling). Both subtest scores can be converted into a gross motor quotient (GMQ). Each skill was executed twice and evaluated based on 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. A GMQ less than 85 indicates performance below the 15thpercentile. The TGMD-2 shows good psychometric qualities in order to assess the gross motor skill performance of typically developing children (Evaggelinou, Tsigilis, & Papa, 2002; Ulrich, 2000) and children with impairments, including children with mild ID (Simons et al., 2008). In the present study, Cronbach’s Alpha for the locomotor subset was a = .82 (DS a = .73, TD a = .72), for the object control subset a = 79 (DS a = .59, TD a = .01) and for the gross motor quotient a = .89 (DS a = .80, TD a = .54) (Ulrich, 2000). 2.2.2. Movement Assessment Battery – 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 school settings, but can be completed by teachers, parents or professionals as an informal assessment of motor performance. It 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 from five to 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: (A) movement in a static and/or predictable environment; (B) 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 (C) relates to non-motor factors that might affect movement, e.g. lack of confidence and impulsiveness. The total motor score (TMS) equals 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 of or above 50 are highly likely to have a motor impairment in their daily lives; children with scores between 35 and 50 are ‘at risk’ of having a motor impairment; and children with scores of 35 or lower have no detectable motor impairment. Cronbach’s Alpha for both groups in this study was .93 for all 43 items together, .89 for Section A, .91 for Section B, and .56 for Section C. These are sufficiently high, suggesting that the items of the Checklist measure the same construct.

1

http://apps.nccd.cdc.gov/dnpabmi/Calculator.aspx?CalculatorType=Metric.

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2.3. Procedure Data was collected in the gyms of the schools. The children had not attended any motor activity earlier and were properly dressed in sports gear and running shoes. All safety measures with regard to the physical activity of the young participants who participated in the survey were taken and external noise as a distraction was minimized. Each child was assessed individually in hours and on days agreed upon by the head of the schools. In addition, there were meetings held with all the school children with the aim of familiarizing them with the examiner, and reducing anxiety during the examination, before the measurements. In order to ensure such an 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 keep the child’s interest high and to eliminate any stress, in order to assess the child in accordance with the instruction manual. 2.4. Data analysis The statistics were compiled using SPSS software (version 19.0) and a significance level of .05. To analyze between-group and gender differences in motor performance (children with DS and TD children), ANCOVAs were conducted on the TGMD-2 locomotor and object-control subtest raw scores as well as the MABC-C scores, with age and BMI percentiles as covariates. In order to determine the meaningfulness of group effects for the TGMD-2 correlational effect sizes were calculated for each dependent variable in accordance with Rosnow, Rosenthal, and Rubin (2000). An effect size correlation of r = .10 was defined as small, r = .30 as moderate, and an effect size of r = .50 as large (Field, 2005). A Pearson correlation was calculated for each research question to measure associations between the TGMD-2 and the MABC-C. Correlations were deemed significant if p < .05. A crosstab analysis of percentile scores for total performance on each assessment was conducted to determine the level of agreement between the assessments to classify children as at-risk. 3. Results 3.1. Test of Gross Motor Development The TGMD-2 locomotor and object-control subtest scores of the three groups are presented in Table 3. Significant differences were obtained between the children with DS and the TD children in both TGMD-2 subtests. The children with DS scored significantly lower than the TD children, with effect sizes being large for the children with DS (locomotor skills r = .70, object-control skills r = .83). Locomotion and object control scores were significantly correlated in the group of the TD children (r = .60) and the children with DS (r = .45), but up to a moderate degree. From the analysis per test item, it appeared that the children with DS scored significantly lower on all test items compared to TD children. The effect sizes were large for the run (r = .51), the hop (r = .74), the horizontal jump (r = .54), and the roll (r = .58) as well as dribble (r = .79), catch (r = .61), kick (r = .52), overhand throw (r = .56), and underhand roll (r = .37). Small to medium effect sizes were found for the gallop (r = .37), leap (r = .36), the slide (r = .41), and striking (r = .29). When gender differences were examined for the test scores, boys of the children with DS were better performers of the run, the gallop, the leap, the catch as well as the locomotor and object-control skill sum scores, whereas girls of the TD group were more proficient in these areas (see Fig. 1). According to the TGMD-2 performance descriptors for subtest standard scores, in the group of the TD children, three children (17%) were classified as poor, one (6%) as below average, ten (56%) as average, and four (22%) as above average, whereas in the group of the children with DS twelve (67%) were classified as very poor, five children (28%) as poor, and one (6%) as average (CHI2(4) = 24.9, p < .001). 3.2. Movement Assessment Battery – Checklist On most items of Section A, children with DS exhibited significantly more problem behavior than the TD children (see Fig. 2). The highest effect sizes after controlling for age, gender, and BMI percentiles were found for the item ‘‘Forms letters using a pencil or pen’’ (r = .88), followed by the items ‘‘Uses scissors to cut paper’’ (r = .84), ‘‘Hops on either foot’’ (r = .79), ‘‘Fastens buttons’’ (r = .78), ‘‘Throws a beanbag or ball so that another stationary child can catch it’’ (r = .67), ‘‘Manipulates small objects’’ (r = .66), ‘‘Maintains balance while standing to pull on articles of clothing’’ (r = .58), and ‘‘Puts on articles of clothing over the head’’ (r = .56) indicating large effects. On almost all items of Section B, children with DS exhibited significantly more problem behavior than the TD children (see Fig. 3). The highest effect sizes after controlling for age, gender, and BMI percentiles were found for the item ‘‘Throws a ball while on the move so that another child can catch it’’ (r = .85), followed by the items ‘‘Continually bounces and keeps control of a large playground ball’’ (r = .83), ‘‘Hits/strikes a moving ball using a bat or racquet’’ (r = .80), ‘‘Moves body in time with music or other people’’ (r = .75), ‘‘Catches a ball’’ (r = .65), ‘‘Participates in dodging and chasing games’’ (r = .54), ‘‘Maintains balance when frequent adjustments are required’’ (r = .53), ‘‘Keeps time to a musical beat by clapping hands or tapping feet’’ (r = .52), and ‘‘Participates in a team game using skills of throwing, catching, kicking or striking’’ (r = .51) indicating large effects. Only for the passive (r = .31) and distractible (r = .31) items of Section C, did children with DS show a tendency toward exhibiting significantly more problem behavior than the TD children (see Fig. 4). The effect sizes after controlling for age, gender, and BMI percentiles for these two items indicate moderate effects.

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Table 3 Mean TGMD-2 test scores by group, controlled for age, gender and BMI percentiles. DS (n = 18) M  SD

TD (n = 18) Min–Max

M  SD

Stat. analysis Min–Max

Sex

BMI

Group  sex

p = .001, h2p ¼ :335 p = .006, h2p ¼ :223 p < .001, h2p ¼ :575 p = .014, h2p ¼ :185 p < .001, h2p ¼ :341 p < .001, h2p ¼ :211

ns ns ns ns ns ns

ns ns ns ns ns ns

ns ns ns ns ns ns

F(1,30) = 4.48, p = .043, h2p ¼ :130 F(1,30) = 5.68, p = .024, h2p ¼ :159 ns F(1,30) = 4.08, p = .053, h2p ¼ :120 ns ns

28–48 3–13 1–84

F(1,30) = 39.6, p < .001, h2p ¼ :569 F(1,30) = 42.2, p < .001, h2p ¼ :585 F(1,30) = 31.7, p < .001, h2p ¼ :514

ns ns ns

ns ns ns

ns ns ns

F(1,30) = 6.55, p = .016, h2p ¼ :179 F(1,30) = 6.84, p = .014, h2p ¼ :186 F(1,30) = 8.48, p = .007, h2p ¼ :220

8.61  1.38 6.89  1.18

6–10 4–8

F(1,30) = 4.29, p = .047, h2p ¼ :125 F(1,30) = 52.0, p < .001, h2p ¼ :634

ns ns

ns ns

ns ns

0–6 4–8 1–8 2–8

5.67  0.59 7.67  0.69 6.44  0.70 6.83  1.20

4–6 6–8 6–8 5–8

F(1,30) = 28.3, F(1,30) = 12.6, F(1,30) = 12.5, F(1,30) = 20.1,

p < .001, h2p ¼ :486 p = .001, h2p ¼ :295 p = .001, h2p ¼ :295 p = .001, h2p ¼ :402

ns ns ns ns

ns F(1,30) = 3.27, p=.081, hp2=.098 ns ns ns ns

ns ns ns ns

F(1,30) = 4.33, p = .046, h2p ¼ :126 ns ns ns

18–41

42.1  2.47

37–45

F(1,30) = 80.3, p < .001, h2p ¼ :728

ns

5.33  1.85 5.28  2.24 2.78  3.32 3.28  1.81 4.33  2.83 6.28  2.54

2–8 0–8 0–10 0–6 0–8 0–8

7.22  1.40 6.61  0.92 8.39  1.61 4.50  1.47 7.22  1.70 7.90  0.47

4–8 5–8 4–10 2–6 2–8 6–8

Raw Standard Percentile

27.2  9.74 3.89  2.97 7.89  19.2

8–47 1–13 1–84

41.8  5.16 9.67  3.11 48.0  31.9

Object control skills Striking a stationary Ball Dribble

7.72  1.64 2.50  2.23

4–10 0–8

Catch Kick Overhand throw Underhand roll

3.33  2.11 6.66  1.29 4.50  1.98 4.89  1.60

Raw

29.4  6.30

Group F(1,30) = 15.1, F(1,30) = 8.61, F(1,30) = 40.5, F(1,30) = 6.83, F(1,30) = 15.5, F(1,30) = 8.02,

Standard Percentile

4.06  2.18 5.44  6.43

1–8 1–25

9.89  1.88 49.1  21.1

6–13 9–84

F(1,30) = 87.2, p = .001, h ¼ :744 F(1,30) = 101, p < .001, h ¼ :771

ns ns

F(1,30) = 3.98, p=.055, hp2=.117 ns ns

Total Sum of Standard Scores Gross Motor Quotient Percentile

7.94  4.44 63.8  13.3 4.11  9.58

2–19 46–97 1–42

19.6  4.49 98.7  13.5 48.1  29.1

12–26 76–118 5–89

F(1,30) = 78.5, p < .001, h2p ¼ :723 F(1,30) = 78.5, p < .001, h2p ¼ :723 F(1,30) = 62.8, p < .001, h2p ¼ :677

ns ns ns

ns ns ns

2 p 2 p

ns

ns

ns ns

ns F(1,30) = 2.44, p = .021, h2p ¼ :126

ns ns ns

F(1,30) = 5.61, p = .024, h2p ¼ :158 F(1,30) = 5.61, p = .024, h2p ¼ :158 F(1,30) = 11.6, p = .002, h2p ¼ :279hp2=.279

N. Schott et al. / Research in Developmental Disabilities 35 (2014) 3299–3312

Age

Locomotor skills Run Gallop Hop Leap Horizontal Jump Slide

[(Fig._1)TD$IG]

N. Schott et al. / Research in Developmental Disabilities 35 (2014) 3299–3312

3307

100

DS

TD

90 80

TGMD-2 (percentile)

70 60 50

40 30 20 10 0 boys

girls

boys

locomotion

girls

boys

object control

girls total

Fig. 1. Mean TGMD-2 subtest scores and standard deviations by group and gender, controlled for age and BMI percentiles.

Section A: movement in a static and/or predictable environment 2,50 ** **

2,00

DS TD

** **

4-point scale (0-3)

[(Fig._2)TD$IG]

Test of Gross Motor Development

1,50

**

1,00 ** ,50

**

** *

**

ns

T

ns

ns

,00

Fig. 2. Mean MABC checklist Section A scores by group, controlled for age, gender, and BMI percentiles (**p < .01, *p < .05, Tp < .10).

ns

[(Fig._3)TD$IG]

N. Schott et al. / Research in Developmental Disabilities 35 (2014) 3299–3312

3308

Section B: movement in a dynamic and/or unpredictable environment 2,50

** **

DS TD

4-point scale (0-3)

2,00

**

1,50 **

** 1,00

**

** **

**

** ,50

ns

*

ns

,00

Fig. 3. Mean MABC checklist Section B scores by group, controlled for age, gender, and BMI percentiles (**p < .01, *p < .05, Tp < .10).

Group differences on the MABC checklist with analysis of covariance (ANCOVA) – controlled for age, gender, and BMI percentile revealed that the children with DS scored significantly more poorly in sections A and B, and the Total Motor Score, but not on Section C (see Table 4). No main effects with regard to age, gender, or BMI percentiles were found for the Sections A, B, or the TMS-score. A significant interaction was found for group x gender for Section A, with boys (M = 12.4, SD = 5.75) of the children with DS being better performers than girls (M = 17.1, SD = 5.64), whereas girls (M = 0.57, SD = 1.13) of the TD group were more proficient than the boys (1.55  1.51) (Fgroup  gender(1, 30) = 4.47, p = .043, h2 = .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 = .063, h2 = .110. Large effect sizes after controlling for age, gender, and BMI percentiles were found for Section A (r = .86), Section B (r = .84), and the Total Motor Score (r = .86), but not for Section C (r = .13). Sections A–C scores were significantly correlated in the group of the TD children (A and B: r = .74; A and C: r = .78; B and C: r = .51) and the children with DS (A and B: r = .78; A and C: r = .48; B and C: r = .52), up to a moderate to high degree. The Total Motor Score is interpreted using a traffic light system: Class teachers and physical education teachers identified n = 17 (94.4%) children with DS 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 n = 2 (11.1%) were classified as highly likely to have movement difficulty, n = 2 (11.1%) as being at risk of movement difficulty, and n = 14 (77.8%) as having no movement difficulty (green).

Table 4 Mean MABC checklist subscores and standard deviations by group, controlled for age, gender, and BMI percentiles. DS

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

TD

Stat. analysis

M  SD

Min–Max

M  SD

Min-Max

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, Fgroup(1,30) = 73.3, Fgroup(1,30) = 0.75, Fgroup(1,30) = 96.4,

p < .001, h2 = .766 p < .001, h2 = .710 p = .394, h2 = .024 p < .001, h2 = .763

[(Fig._4)TD$IG]

N. Schott et al. / Research in Developmental Disabilities 35 (2014) 3299–3312

3309

Section C: non-motor factors that might affect movement ,90 T DS TD

,80 ns

yes/no-scale (0-1)

,70

ns

,60

ns

,50 T ,40

ns ns

ns

ns ns

ns

,30

,20 ns ,10 ns ,00

Fig. 4. Mean MABC checklist Section C scores by group, controlled for age, gender, and BMI percentiles (**p < .01, *p < .05, Tp < .10).

3.3. Relationship of TGMD-2, and MABC checklist Table 5 reports the correlations between the different indices of the standardized motor skills (TGMD-2: percentile, MABC-C) regarding the sample of children with DS and TD children. As can be seen, significant correlations were found for the sample of TD children across each of the performance-based motor indices with Section A and Section C, except for Section B. In contrast to that, no significant correlations were found Table 5 Correlations (r) and difference in magnitude of correlations (Fisher’s z) across bottom-up and top-down motor indices for the sample of typically – developing control children (N = 18) and children with Down Syndrome (N = 18). MABC checklist (top-down assessment)

TGMD-2 – bottom up Locomotion DS r TD r z** Object control DS r TD r z** GMQ DS r TD r z**

Section A

Section B

TMS

Section C

.55* .58* 0.12

.44T .21 0.71

.53* .38 0.52

.25 .55* 0.99

.30 .51* 0.69

.15 .41T 0.78

.24 .48 0.76

.21 .43T 0.68

.55* .50* 0.19

.29 .58* 1.00

.57* .65** 0.35

.47* .35 0.40

* p < .05. ** A z-obtained of 1.972244 would be statistically significant at p < .05. p < .10.

T

[(Fig._5)TD$IG]

N. Schott et al. / Research in Developmental Disabilities 35 (2014) 3299–3312

3310

Group

60

below poor average

very poor

average

above average

Down Syndrom TD

Total Motor Score (A+B)

50

40

30

20

10

0 40

60

80

100

120

TGMDQuotient Fig. 5. Relationship between bottom-up and top-down motor skills (TMC) in the sample of typically-developing (TD) children and children with Down Syndrome (DS). Dark filling = TMS red zone; medium filling = TMS amber zone, light filling = TMS green zone.

with the children with DS for Section C and the TGMD-2. Significant correlations with regard to the Section A, B, and the TMS were found only for the subscore locomotion and the GMQ. However, it is apparent – taking a closer look at Table 5 – that the magnitude of correlations found for the TD children was stronger than those of the children with DS for 8/12 (67%) comparisons. In order to test if there was a difference in significance pattern across the motor test correlations, Fisher’s z was applied to each pair of correlations (i.e. DS r compared to TD r per correlation). Results revealed no significant difference for each pair of correlations, illustrating that the pattern of strength of correlation did not differ significantly across the children with DS and TD sample for each of the motor skill indices. Similar correlations were found for the General Motor Quotient and the Total Motor Score for the children with DS and the TD-group, in particular, which did not differ significantly. This suggests that the standard scores for performance- and teacher-based assessments produced by both groups fall within the same distribution, as is clearly illustrated in Fig. 5. Furthermore, Fig. 5 clearly demonstrates a greater interindividual variability in motor competence of the children with DS, both in Total Motor Score and TGMD Quotient. It should be noted that two of the children with DS achieve similar results to those of the TD children, with one of them being ‘‘average’’. In contrast, the TD group is characterized by a smaller variability and only for the TGMD Quotient. 4. Discussion In the current study we have analyzed and compared the motor competence of children with DS and TD children using a combination of a performance-based and teacher measures, as recommended by Kennedy et al. (2013). Applying both approaches in combination seems to be beneficial for the following reasons: The top-down approach reflects a long-term impression of the child’s fine and gross motor competence in a broader context. On the contrary, the bottom-up approach provides a ‘‘snapshot’’ of the current motor competence assessed with more sport-specific items in a situation which could be perceived by the children as a test. Overall, TD children achieve consistently better results compared to children with DS, both in the TGMD-2 and MABC-C, which differ significantly in most cases. Boys with DS were better performers of the run, gallop, leap, and catch as well as the locomotor and object-control skill sum scores compared to the girls with DS, whereas girls of the TD group were more proficient in these areas. TD children achieve significantly better results in 21 out of 28 items of Section A + B of the MABC-C, compared to the children with DS; whereas there are no significant differences for Section C (non-motor factors). Our results show more significant relationships between TGMD-2 and MABC-C subscores and overall scores for the TD sample compared to the children with DS. The significantly better results in all locomotor and object control skills of the TD children compared to the children with DS confirm the results of previous studies (e.g. Hasan et al., 2012). Additionally, the girls of the TD sample achieve better

N. Schott et al. / Research in Developmental Disabilities 35 (2014) 3299–3312

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results in both subdimensions and the total score of the TGMD-2 than the boys. Although the participants of our study are one year older (nine vs. eight, on average), than the children in the study of Tiernan (2012), the TD children achieve similar results for the locomotor and object control scores. In contrast, the children in our study with DS score about 4.5–6 points more, which is a substantial developmental difference. Nevertheless, these results should be interpreted with caution, due to the small sample sizes. Palisano et al. (2001) report the fastest gross motor function improvement for children with DS until the age of six. Accordingly, children with DS actually show a delayed motor development (e.g. Volman et al., 2007), but a further improvement as well. Furthermore, the children with DS show consistently larger standard deviations, which confirm the greater interindividual variability in motor skills and abilities in children with DS reported by Dolva et al. (2004) and Volman et al. (2007). This view is supported by the results illustrated in Fig. 5, in which a few exceptions of the DS and TD group attain similar scores. These findings support the need of tailor-made therapies and interventions, considering the child’s unique motor profile (Davis, 2008; Kennedy et al., 2012). Regarding the teacher-report measures of the MABC-C, TD children achieve significantly better results in 21 out of 28 items (Section A + B), compared to the children with DS, whereas there are no significant differences for Section C (non-motor factors). The strongest differences in Section A are observed for three fine motor items (‘‘Fastens buttons’’, ‘‘Forms letters using a pencil or pen’’ and ‘‘Uses scissors to cut paper’’), which is consistent with the results of Dolva et al. (2004), Spano` et al. (1999) and Volman et al. (2007). Additionally, the item ‘‘Hops on either foot’’, which requires dynamic balance/postural control, shows a great effect size, which matches with the findings of Volman et al. (2007) and Wang et al. (2012). The greatest problem in Section B appears for three dynamic object-control/manipulation skills (‘‘Hits/strikes a moving ball using a bat or racquet’’, ‘‘Throws a ball while on the move so that another child can catch it’’ and ‘‘Continually bounces and keeps control of a large playground ball’’), for both TD and DS children. However, children with DS obtain significantly lower results. An explanation could be that manipulating an object, as is the case in these items, requires the ability to anticipating spatial-temporal interrelations and a raised capacity to process visual information (Lo´pez-Moliner, Brenner, Louw, & Smeets, 2010). It is known that perceptual-motor impairments are attributed to individuals with DS (Lawrence, Reilly, Mottram, Khan, & Elliott, 2013). The significantly different scores of both samples are noticeable but the profile for the different aspects of the non-motor factors is very similar for TD children and children with DS. Related to this, it could be assumed that children with DS could achieve similar results compared to TD children, but they could be just temporally delayed. As mentioned before, this assumption is supported by the results presented in Fig. 5 and matches the conclusion of Palisano et al. (2001). Overall, the teacher’s perspective seems promising (Kennedy et al., 2012): because they spend a lot of time with the children, they are able to compare one child with their classmates in an everyday context and are also interested in supporting the development of the children. Furthermore, it can be assumed that teachers rate the children more objectively than their parents and they probably do not answer according to social desirability (Morsbach & Prinz, 2006). With regard to the analysis of the relationships between the MABC-C and locomotion, object-control scores and GMQ of the TGMD-2, there are several significant correlations for children with DS and TD. Therefore our results are slightly higher than the correlations between MABC-2 checklist and BOT-2 scores of Kennedy et al. (2012) for TD children. Our results show that there tend to be more significant relationships for the TD sample compared to the children with DS (67% vs. 50%). Although results revealed no significant differences across the children with DS and the TD sample for each of the motor skills indices, the correlations of the object control skills are particularly noticeable. For this subdimension, children with DS show no significant and lower negative relationships, compared to TD children. These data could possibly be explained by a greater variability with regard to ball skills reported for children with DS (Spano` et al., 1999) and different degrees of perceptual-motor impairments, which might be more visible in a performance-based assessment, but difficult to identify with a top-down approach. 4.1. Study limitations and future research Although the sample size of our study is similar to previous studies (cf. Table 1), more participants 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 and cognitive impairments (Dolva et al., 2004; Patterson et al., 2013; Volman et al., 2007). The cross-sectional design of this study could be evaluated as an adequate approach providing first data about the relationship between performance-based and teacher-report measures in this field. Future research is required to confirm the observed relationships. Studies with a longitudinal design should examine the stability of applying these two approaches throughout the course of time. Furthermore, it seems reasonable to study whether the suggested advantages of the teacher-report measure, compared to the parent-report measure, actually exist. 5. Conclusion In conclusion, the present study was an initial investigation applying a teacher-report and performance based measure of motor skills in TD children and children with DS. The combination of both approaches reflects both a ‘‘snapshot’’ of the current motor competence (bottom-up) and a long-term impression (top-down). Regarding both methods separately, we could confirm the results of previous studies (cf. Table 1). The relationships between both approaches were strong enough to

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classify the combined use of both methods as useful in getting a more detailed picture of the child’s individual motor profile – keeping the creation of tailor-made therapies and interventions for each child (Davis, 2008) in mind. This seems particularly important if a few children with DS achieve similar results to TD children, but could be significantly worse in different degrees as well. Furthermore, the individual advancement of every child could help to reduce barriers to participation in physical activity (Barr & Shields, 2011). The positive effects of the few intervention studies that exist (e.g. Gupta et al., 2011; Passarini, 2001) support this assumption. References Arbuckle, R., & Abetz-Webb, L. (2013). Not just little adults: Qualitative methods to support the development of pediatric patient-reported outcomes. Patient– Patient-Centered Outcomes Research, 6(3), 143–159. Barr, M., & Shields, N. (2011). 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Motor skill assessment in children with Down Syndrome: relationship between performance-based and teacher-report measures.

of previous studies show a large interindividual variability with regard to motor skills and motor abilities in children with Down Syndrome (DS). In o...
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