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The Clinimetric Properties of Performance-Based Gross Motor Tests Used for Children With Developmental Coordination Disorder: A Systematic Review

Slater, Leanne M. BPhty (Hons); Hillier, Susan L. PhD; Civetta, Lauren R. BPhty (Hons), Grad Dip Pub Hlth

doi: 10.1097/PEP.0b013e3181dbeff0
Review Article

Purpose: Performance-based measures of gross motor skills are required for children with developmental coordination disorder to quantify motor ability and objectify change. Information related to psychometrics, clinical utility, feasibility, and client appropriateness and acceptability is needed so that clinicians and researchers are assured that they have chosen the most appropriate and robust tool.

Methods: This review identified performance-based measures of gross motor skills for this population, and the research evidence for their clinimetric properties through a systematic literature search.

Results: Seven measures met the inclusion criteria and were appraised for their clinimetric properties. The Movement Assessment Battery for Children and the Test for Gross Motor Development (second version) scored highest on appraisal.

Conclusions: The 2 highest scoring measures are recommended in the first instance for clinicians wishing to evaluate gross motor performance in children with developmental coordination disorder. However, both measures require further testing to increase confidence in their validity for this population.

This systematic review of the properties of measures used to document motor performance in children with DCD indicates the 2 best measures available for use by clinicians and researchers: the M-ABC and the TGMD-2.

Centre for Allied Health Evidence, School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia

Correspondence: Susan L. Hillier, PhD, Centre for Allied Health Evidence, School of Health Sciences, University of South Australia (City East), GPO Box 2471, Adelaide, South Australia 5001, Australia (

This systematic review was completed as partial fulfillment of the Bachelor of Physiotherapy with Honors by Leanne Slater (Nee Plummer) at the University of South Australia.

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Historically, outcome measures were used primarily to assess quality of care through numbers of morbidities, mortalities, readmissions, and length of stay.1 More recently, outcome measures have been developed to assess health care interventions by measuring physical, social, and psychological health factors to encompass the World Health Organization's definition of health.1,2

Changes in funding models, management, and national health strategies have increased the importance of implementing outcome measures to evaluate interventions used in health care facilities.3,4 Health practitioners are increasingly being pressured to use appropriate outcome measures to assess patient's progress and justify funding.4 This includes pediatric physiotherapy as children with suspected developmental coordination disorder (DCD) are often referred for gross motor assessment and intervention.

DCD is a term used to describe children who exhibit insufficient motor coordination skills in comparison with that expected for their chronological age and intellect and for which there are no attributable medical disorders.5 The motor impairments (MIs) are at a level at which activities of daily living and/or academic achievement are significantly negatively affected.5 The prevalence of DCD is estimated to range from 5% to 9% of school-age children.6,7

Children with DCD form a heterogeneous group, and individuals tend to be deficient in a variety of motor tasks.8 These children commonly withdraw from physical, academic, and social activities because of their motor deficits, fear of failure, and peer criticism. Consequently, poor academic performance, low levels of perceived competence, low self-esteem, deficient social skills, and reduced physical fitness and strength often ensue.8,9

Evidence suggests that without intervention, motor deficits and problems associated with DCD are not always outgrown in adolescence and can persist into adulthood.10–12 Thus, appropriate outcome measures to help monitor changes in gross motor development in response to intervention are required. This will enable health practitioners to manage individuals with DCD effectively and to justify funding of intervention.

Gross motor skills can be measured through formal and informal means.13 Informal assessments have no standard procedure, are generally flexible, and can provide useful qualitative information, but they can be time-consuming and are generally not suitable when comparing results across individuals.13 Examples include interviews and general/teacher observations.13 Formal tests are standardized with strict testing procedures and are used to diagnose, make intervention decisions, and/or evaluate intervention.13 Performance-based tests are a common type of formal measure used to assess children's gross motor skills.14 A performance-based gross motor measure assesses a child's ability in a variety of motor skill domains by determining the child's performance on a specific test administration.14

The quality and weighting of the information gained from an outcome measure depends, in part, on the psychometric properties of the test.15 The most trustworthy tools have a strong level of measurement and established validity, reliability, and responsiveness in the population being tested.1,15

All standardized tests provide a measure that is scaled. One definition states that “a measurement is obtained by applying a standard scale to variables, thus translating direct observations or patient/proxy reports to a numerical scoring system.”15 Therapists need to ensure that numbers obtained from outcome measures are used in a valid and meaningful way.15 A test that is valid accurately measures the domain that it is intended to measure.16 Validity can be demonstrated by showing that the measure correlates significantly with another test that measures the same constructs (criterion validity, which can be assessed with concurrent or predictive validity), experts in the area agree that the items in the test are representative of the whole domain that the test claims to measure (content validity), the test seems to test what it is meant to by using subjective factors (face validity), and the test measures an abstract concept or construct (construct validity).1,15–17 Acceptable construct validity is demonstrated when the test identifies a characteristic that it claims to measure within a population that is known to have that characteristic (known group method), by demonstrating that 2 tests that measure the same construct correlate well (convergent validity), that 2 tests that do not measure the same construct do not correlate well (discriminative validity), or by factor analysis in which statistical analysis demonstrates that the items on a test can be grouped to fit into related components or factors.1,15–17

A test is reliable when it demonstrates that test scores are stable over time (test-retest reliability) and with different examiners (interrater reliability).1,15–17 A reliable test will also have internal consistency, where the degree to which test items all measure the same construct is adequate.1,15 Finally, a test should at an appropriate level of difficulty be able to demonstrate change (responsiveness) and be able to accurately discriminate a person with a positive impairment (sensitivity) or no impairment (specificity).1,15

A test that is viable clinically should be practical to use. Tests that show excellent psychometric properties may not be feasible due to complicated equipment requirements, long administration times, difficult application/scoring systems, and/or difficulties with interpretation of scores. Additionally, the measure needs to be acceptable and meaningful to the patient/client. Thus, these clinimetric factors also need to be taken into consideration when a clinician selects an appropriate test.

There are several performance-based measures used clinically and in research to investigate or monitor the motor coordination of children with DCD. However, it is important that decisions for the choice of one measure over another are based on the principles outlined earlier. Nevertheless, after an extensive search of the literature, no reviews were identified that investigated this. Thus, to identify performance-based measures of gross motor function and to determine the relative strength of these measures, we conducted secondary research. This was undertaken using a systematic review and appraisal approach. The aims were to systematically identify (1) performance-based outcome measures that assess gross motor skills of children with DCD, (2) literature reporting on the psychometrics of the identified measures in the DCD population and to evaluate the quality of these studies, and (3) the most robust outcome measure based on evaluation of the literature identified.

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Inclusion and Exclusion Criteria for Considering Studies

Outcome measures were included in the review if they met the following criteria: (1) a standardized performance-based gross motor assessment suitable for children with MIs consistent with DCD, (2) printed in English, (3) a test that identified DCD and measured changes in gross motor performance of children (for composite tests, at least 50% of the overall suite must be gross motor), (4) for children older than 4 years, and (5) the most recent version reported in the published literature searched.

Studies were included if they (1) assessed psychometric properties of any of the measures that met the aforementioned inclusion criteria, (2) were published in English in a peer-reviewed journal between January 1980 and February 2008 (the date 1980 was chosen to exclude those measures that do not reflect current thinking regarding motor performance13), and (3) if participants were aged between 4 and 16 years. Studies that used normative samples were included when relevant, for example, to gather normative data or when the population was representational, and therefore included children with motor difficulties. Such studies are clearly identified in the results. Studies were excluded if (1) the majority of participants had been diagnosed with a disorder other than DCD or equivalent DCD term (ie, cerebral palsy, Down syndrome, and autism were excluded), (2) the performance-based assessment was used as a criterion measure for a screening tool or nonmotor performance-based test, or (3) the studies were published before 1980 because it was thought that the information would pertain to a generation different from the current child population and a different philosophical approach to motor skills.

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Search Strategies

A systematic search of computer databases was used to locate studies. The databases searched were MEDLINE, AMED, Meditext, Ausport, Ausportmed, Humanities and Social Science Collection, A+ Education, CINAHL, Academic Search Premier, SPORTdiscus, ERIC, Health Source: Consumer Edition, Health Source: Nursing/Academic Edition, PsycINFO, Current Contents Connect, Blackwell Synergy, Cochrane, PEDro, OTseeker, EMBASE, and Scopus. Pearling of the reference lists of all retrieved studies was also performed.

Three groups of search terms were used; outcome measurement, DCD or associated terms, and psychometric properties (separated by Booleans “OR” and “AND”). A full list of search terms have been included in Table 1. The search was conducted between February 4 and 8, 2008.



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Critical Appraisal

Tool to Identify and Evaluate Measures.

The Measurement Critical Appraisal Tool (MCAT) was used to identify and then evaluate the outcome measures in separate processes (Table 2). This tool was modified to suit the needs of this review from a version of the criteria developed by the United Kingdom's Clearing House on Health Outcomes.18



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Tool to Appraise the Quality of Studies.

The quality scoring of the studies evaluating each measure was carried out using a modified critical appraisal tool from the NHMRC Handbook series.19 This tool is referred to as the Quality Critical Appraisal Tool (QCAT) (a copy of the tool can be obtained from the authors).

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Data Extraction and Synthesis

Descriptive data on the clinimetrics and psychometrics of outcome measures were extracted from the included studies by the first reviewer and entered into separate spreadsheets. Two reviewers then appraised all articles using both the MCAT and the QCAT tools. If disagreements arose between scorers, then a third reviewer was available to facilitate consensus. This was not necessary.

The outcome measures quality score (MCAT) was obtained from summing scores for validity (3 points), reliability (3 points), responsiveness (1 point), precision (1 point), client centeredness (2 points), and tester centeredness (2 points). Half scores were given if part of an item was achieved (maximum score of 12; Table 2). Acceptable statistical analysis and results for each metric were defined a priori to determine whether each criterion was met positively (available from authors).

Risk of bias (quality scoring using the QCAT) was determined using 3 defined areas including selection, analysis, and measurement bias. Three points were allocated to each area based on set criteria (Table 3). The scores from each area were summed to give a total risk of bias score, the scores were categorized as follows: low risk of bias, score 7 to 9; moderate risk of bias, score 5 to 6; and high risk of bias, score 3 to 4 (maximum score of 9). Individual studies were scored and reasoning was reported descriptively.



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Identification of Outcome Measures

The preliminary search resulted in the identification of 26 potential assessments that measured motor skills of children. Through consultation with 2 experienced pediatric physiotherapists, 13 outcome measures met the 5 outcome measure inclusion criteria listed earlier, and the other 13 were excluded as they clearly were not designed for children with DCD, were not gross motor performance tests, or were a previous version of an included measure. If there was any disagreement about whether the outcome measure should be excluded, the assessment name was still included in the search to be evaluated more thoroughly using the MCAT. A full list of the 26 measures, with reasons for exclusion, is available from the authors.

After the evaluation on the MCAT, a further 7 measures were excluded. The Sensory Integration and Praxis Test and its predecessor the Southern California Sensory Integration Test were excluded because total composite scores were less than 50% gross motor based.20 The Test of Motor Proficiency was also excluded because it was only used as a screening test.21 No studies meeting the inclusion criteria were retrieved to evaluate the psychometrics of the Ohio State University Scale of Intra-Gross Motor Assessment, Neurosensory Motor Developmental Assessment, Basic Motor Ability Test Revised, or the Cratty 6 Category Gross Motor Tests. An additional outcome measure, the Zurich Neuromotor Assessment (ZNA), was identified during the pearling process and met the criteria for inclusion.

All the outcome measures reviewed represent the most recent versions available in the current literature, with the exception of the Movement Assessment Battery for Children (M-ABC), which has recently been updated in 2007. After consultation with 2 experts in pediatric physiotherapy, it was decided that a 12-month period was not sufficient for the distribution, use, and testing of the M-ABC-2, and, therefore, the first version was evaluated. Thus, a total of 7 gross motor measures were identified: the Basic Gross Motor Assessment (BGMA), Bruininks-Oseretsky Test, 2nd ed. (BOT-2), M-ABC, the McCarron Assessment of Neuromuscular Development (MAND), Peabody Developmental Motor Scale, 2nd ed. (PDMS-2), the Test of Gross Motor Development, 2nd ed. (TGMD-2), and the ZNA. Table 4 outlines the reviewed clinical properties of the test.



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Identification of Literature Reporting on the Psychometrics of the Identified Measures in the DCD Population and Evaluation of the Quality of These Evaluative Studies.

The number of studies identified, the duplicates, and the studies excluded during the search procedure are summarized in the Figure 1. Six manuals meeting the inclusion criteria were identified in the literature, and 5 were obtained from 2 experienced pediatric physiotherapists. The sixth manual for the ZNA was not obtained; however, the authors were contacted and subsequently referred researchers to studies already acquired. The BGMA manual was written in 1979, and thus was excluded.

Fig. 1.

Fig. 1.

The quality of the studies (risk of bias) was evaluated using the QCAT. The number of studies for each measure, QCAT score ranges, and mean total quality scores with standard deviation for each measure are summarized in Table 5. All studies, except 1, were at a low to moderate risk for bias in their reporting. The 1 study scoring poorly was a descriptive report of concurrent validity between the M-ABC and a balance test. The main methodologic problems identified that increased chances of bias in studies were lack of information on tester training and/or blinding and subject recruitment methods. Additionally, many subjects represented samples of convenience and not true representations of the DCD/child populations, thus reducing the generalizability of the results.



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Critical Appraisal of Psychometrics of Each Identified Outcome Measure

Using the MCAT, relevant data on the psychometrics of the outcome measures were extracted from the 33 articles and 5 manuals. Information on the psychometrics of each outcome measure is outlined briefly here. The measurement critical appraisal scores and types of validity, reliability, and responsiveness established are summarized for each outcome measure in Table 6. Information on the population in which validity and reliability were established and user/tester centeredness of individual outcome measures are also summarized in Table 6. For further details, contact the authors. Note that normative data were provided adequately for all outcome measures.



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Validity of Measures

Construct validity of the BGMA was demonstrated through factor analysis, all but 1 item loaded onto 7 factors; however, the BGMA has only 8 tasks, suggesting each item measures a different construct.22 The BOT-2 has moderate to excellent concurrent validity correlations with the PDMS-2 and BOT of Motor Proficiency and adequate content and construct validity demonstrated via item and factor analysis and goodness of fit tests, respectively.23 Concurrent validity correlation coefficients on the M-ABC with other motor tests were moderate to excellent (r = 0.50–1.00) in more than 50% of 13 studies, with 10 of the studies of children with DCD/MI.24,29–40 The lowest correlation coefficients obtained between the M-ABC and other motor tests occurred when the subjects had DCD and/or learning disabilities.33,35,38 Lower correlations also occurred when the M-ABC scores were compared with very specific tests measuring multiple constructs of a particular skill.31,32,37,40

The PDMS-2 and MAND also have moderate to excellent concurrent validity (r ≥ 0.50) with other similar motor measures in studies with DCD/MI.30,36,41 Additionally, the PDMS-2 has moderate to good concurrent validity correlations coefficients with gross motor subtests (r = 0.63–0.75) in typical populations23,26 and adequate results on factor analysis and goodness of fit tests to support its construct validity.26 However, for gross motor components, the MAND only correlated to a fair degree (r < 0.50) with specific motor tests.25,42 In a single study, the TGMD-2 showed support for its concurrent/predictive validity with fair to good correlation coefficients on its subtests and total scores with a similar motor test27 (locomotion r = 0.63 and object control r = 0.41, total scores r = 0.63). The TGMD-2 also has acceptable content validity (through rationale, item analyses and discriminative tests) and construct validity (through factor analysis).27,43,44

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Reliability and Responsiveness of Measures

The BGMA has good to excellent test-retest reliability and interrater reliability (r = 0.97 and 0.99, respectively) in small samples (n = 48 and n = 10, respectively).22 The BOT-2 also has demonstrated good to excellent (r > 0.80) test-retest and interrater reliability correlations.23 Correlations for the test-retest24,34,45–47 and interrater reliability46–49 on total scores of M-ABC are consistently good to excellent (r = 0.72–0.95) in children developing typically and children with MI. The internal consistency of the M-ABC was investigated in a single study that showed the items measured different constructs.50 The M-ABC total scores are reportedly adequately responsive to change45,51 and sensitive45,51; however, subtest and individual item scores have only moderate to low responsiveness to change.51

The PDMS-2 has demonstrated good internal consistency and excellent (r = 0.89) interrater reliability correlations.26,41 The TGMD-2 reportedly has excellent internal consistency and interrater reliability27(r = 0.98). However, for interrater reliability, raters used previously scored protocols and thus only summed and converted scores. Test-retest reliability correlations of the TGMD-2 were good to excellent27 (r = 0.84–0.96). The ZNA test-retest reliability correlations for timed performance scores were good to moderate28,52–54 (r = 0.65) but only fair for scores based on accessory movements28,52–54 (r = 0.45). Inter- and intrarater reliability correlations overall were moderate to excellent for the ZNA; however, some very low correlations (<0.1) were obtained on some items with accessory movement scores.28,52–54

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The search strategies identified several performance-based outcome measures that assess gross motor skills of children with DCD. The critical appraisal process has also indicated which tests are the most robust psychometrically and clinically. The studies identified that investigated outcome measures were nearly all at a low to moderate risk of bias, and thus the results could be considered of acceptable quality.

The M-ABC and TGMD-2 scored equally on overall psychometric and clinical quality ratings. The M-ABC scored well due to demonstrations of adequate sensitivity and because it was the only measure to demonstrate responsiveness to change. The M-ABC has also had its psychometric qualities tested the most of all the measures in the DCD population. Additionally, the M-ABC is quick to set up, administer, and score and requires minimal training, making it a viable tool clinically. The suitability of the M-ABC's US normative data has also been investigated for other cultural groups in a number of studies.39,49,55–59 The M-ABC, however, requires further support for its validity, which should be considered when choosing tests. The M-ABC also seems to have less stable concurrent validity when testing children with DCD and learning disabilities.

The TGMD-2 has demonstrated good psychometric qualities27; however, it is important to note that the investigations were only from the manual and were conducted in children who are typically developing; thus, results have not yet been demonstrated to be as pertinent for children with DCD. Additionally, the reliability between raters administering/scoring performance of children on the TGMD-2 is unreported. The TGMD-2 is reasonably quick to set up and administer, with acceptable additional training requirements for administration and scoring.27 Both these tests give standardized scores that are easily explained to the patient/parent, and both have items that children would find acceptable and relevant.24,27

The BOT-2 scored third and also demonstrated acceptable psychometric qualities, but only 1 study on each psychometric area has been performed, and most were on children who are typically developing.23 The BOT-2 has been reported to have a confusing scoring system and markedly lengthy administration, scoring, and preparation times.60 However, once calculated, the score can be conveyed to the patient adequately.60

The BGMA was ranked fourth in terms of psychometric and clinical quality. Although there is only a single small study investigating the psychometric qualities of BGMA, this test requires minimal equipment and set up and administration time.22 Additionally, the raw score is simply converted into an easy-to-understand percentile.13 However, the BGMA study lacked some methodological rigor as ages were not specified for some areas and sample sizes were small; thus, these factors should be noted if considering this test.

The PDMS-2 was fifth on rankings of overall psychometric and clinical quality. Although it has adequate psychometric properties in children who are typically developing (except for test-retest reliability), its user and tester centeredness have been criticized.30 The PDMS-2 has been reported to require extensive training; additionally, it has a long administration time and purportedly can be difficult to administer and score.26,30 Furthermore, the PDMS-2 also lacked sensitivity in identifying/monitoring children with minor motor dysfunctions.30

The MAND and ZNA were the equal lowest scoring measures. This is partially due to the ZNA lacking formalized validity and the MAND lacking reliability in children. In addition, the MAND scored lower because of some unusual test items along with the extended training time and difficulties with interpretation of the scores.25 The MAND studies were also largely carried out on a small sample of 7-year-old children with typical development, thus caution should be practiced if generalizing these results to other age groups. The MAND, however, has demonstrated adequate sensitivity in identifying MI in 4- to 5-year-old children.36 The ZNA is currently lacking in psychometric rigor. Investigations into its reliability involved a small sample size of typical children and some items showed questionable correlations on interrater and test-retest reliability, the same reliability results are published in 4 separate publications.28,52–54 The ZNA also scored lower on its tester centeredness due to difficulties with scoring accessory movements and the extended training required.28,52–54

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Summary and Implications for Research and Clinical Practice

Overall, none of the outcome measures identified scored perfectly; all had redeeming factors along with their flaws. When choosing the most appropriate test, it is important for a clinician or researcher to consider not only which psychometric properties have been demonstrated adequately but also what population and age group have been investigated. Additionally, the practicality of the clinical qualities of a test should be taken into account when selecting an assessment for a particular patient.

We recommend that the M-ABC and the TGMD-2 should be considered for assessing the gross motor performance of children with DCD in the first instance, but also recommend further studies be conducted to clarify the psychometric qualities of these tests. Specifically, the M-ABC needs further evidence of its validity, and the TGMD-2 requires psychometric testing with children with DCD to enable stronger justification for use in this population.

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The completion of this review in its current form was only possible through the support and assistance of Liz Pridham, Emily Ward, and Auburn McIntyre.

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child; developmental coordination disorder; human movement system; motor skills disorders; outcome measures; psychomotor performance; validation studies as topic

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