Aertssen W, Bonney E, Ferguson G, Smits-Engelsman B. Subtyping children with developmental coordination disorder based on physical fitness outcomes. Hum Mov Sci. 2018 Aug;60:87-97. doi: 10.1016/j.humov.2018.05.012. Epub 2018 May 28. PubMed PMID: 29852337. 2:
Bonney E, Ferguson G, Smits-Engelsman B. Relationship between Body Mass Index, Cardiorespiratory and Musculoskeletal Fitness among South African Adolescent Girls. Int J Environ Res Public Health. 2018 May 28;15(6).
Bonney E, Aertssen W, Smits-Engelsman B. Psychometric properties of field-based anaerobic capacity tests in children with Developmental Coordination Disorder. Disabil Rehabil. 2018 Mar 6:1-12. doi: 10.1080/09638288.2018.1446189
Bonney E, Rameckers E, Ferguson G, Smits-Engelsman B. "Not just another Wii training": a graded Wii protocol to increase physical fitness in adolescent girls with probable developmental coordination disorder-a pilot study. BMC Pediatr. 2018 Feb 22;18(1):78.
Link between DCD subtypes and fitness levels
Aertssen W, Bonney E, Ferguson G, Smits-Engelsman B. Subtyping children with developmental coordination disorder based on physical fitness outcomes. Hum Mov Sci. 2018 May 28;60:87-97. doi: 10.1016/j.humov.2018.05.012. [Epub ahead of print] PubMed PMID: 29852337. PDF link https://www.sciencedirect.com/science/article/pii/S0167945718300125
Purpose: Children with Developmental Coordination Disorder (DCD) are known to have poor physical fitness. However, differentiating homogenous subgroups of DCD using fitness performance has not yet been established. Therefore the purpose of this study was to identify subtypes in children with and without DCD using measures of physical fitness.
Method:Children (aged 6–10 years, n = 217) constituted the sample for this study. They were assessed on 1) aerobic fitness (20m Shuttle Run test), 2) anaerobic fitness (Muscle Power Sprint Test), 3) isometric muscle strength (handheld dynamometry) 4) functional upper and lower body strength (Functional Strength Measurement) and 5) motor coordination [Movement Assessment Battery for Children-2nd edition (MABC-2) test]. The Ward method was used to identify the various clusters.
Results: Five subtypes emerged in the entire sample. In the typically developing (TD) children mainly 2 subtypes (number 5 and 2) were found containing 89% of the TD children (n = 55), with the largest group demonstrating above average performance on all measures (cluster 5). Children in subtype 2 had just above average motor coordination and good aerobic fitness but lower muscle strength. Subtypes 1, 3 and 4 were clearly “DCD” clusters, however they showed difference in fitness performance. Subtype 1 contained children with DCD who showed poor performance on all fitness outcomes (n = 45). Children with DCD in subtype 3 had poor aerobic but average strength and anaerobic fitness (n = 48). Subtype 4 contained children with DCD (n = 45) who had good muscle strength and anaerobic fitness. Of these, 36% were at risk of DCD while 24% had definite motor coordination problems.
Conclusion: Our findings indicate that children with and without DCD demonstrate heterogeneous physical fitness profiles. The majority of the children (66%) with DCD belonged to subtypes with lower fitness performance. Further studies are needed to confirm these findings in other samples of DCD children.
Hybrid Model of DCD
Wilson, P. H., Wilson, P. H., Smits-Engelsman, B., & Caeyenberghs, K. (2017). Toward a Hybrid Model of Developmental Coordination Disorder, Curr Dev Disord Rep 4:64 PDF via Researchgate
This paper discusses the merits of a hybrid model of developmental coordination disorder (DCD), one that integrates cognitive neuroscience and ecological systems approaches. More specifically, we present an integrative summary of recent empirical work on DCD that enlist behavioural and neuroimaging methods and propose a theoretical interpretation through the lens of a hybrid model. The review identifies two current hypotheses of DCD that find consistent support: the internal modelling deficit (IMD) and mirror neuron system (MNS) accounts. However, motor performance and brain activation patterns are not expressed in a uniform way under these hypotheses—motor deficits are manifested variously as a function of specific task and environmental constraints and condition severity. Moreover, we see evidence of compensatory processes and strategies. Taken together, results support the broad hypothesis that children with DCD show distinct motor control deficits and differences in neural structure and function compared with typically developing children. However, researchers still have difficulty ascribing causation. The proposed hybrid (multi-component) model of DCD can help researchers generate novel hypotheses about specific mechanisms, explaining the constellation of deficits that is shown experimentally and observed clinically. This model can be applied to cognate disorders of childhood that affect movement and design of intervention.
Brain structure and function
Differences in brain structure and function may impact anticipatory planning and reduce automatization of movement skill, prompting greater reliance on slower feedback-based control and compensatory strategies.
Wilson, P., Smits-Engelsman, B., Caeyenberghs, K., Steenbergen, B., Sugden, D., Clark, J., Mumford, N., & Blank, R. (2017). Cognitive and neuroimaging findings in Developmental Coordination Disorder: New insights from a systematic review of recent research. Developmental Medicine and Child Neurology PDF via Researchgate
Aim. To better understand the neural and performance factors that may underlie Developmental Coordination Disorder (DCD), and implications for a multi-component account. Method. A systematic review of the experimental literature published between June 2011 and September 2016 was conducted using a modified PICOS framework. Included were a total of 106 studies. Results. Behavioural data from 91 studies showed a broad cluster of deficits in the anticipatory control of movement, basic processes of motor learning, and cognitive control. Importantly, however, performance issues in DCD were often shown to be moderated by tasktype and difficulty. As well, we see new evidence of compensatory processes and strategies in a number of studies. Neuroimaging data (15 studies, including EEG) showed reduced cortical thickness in the right medial orbitofrontal cortex and altered brain activation patterns across functional networks involving prefrontal, parietal and cerebellar regions in children with DCD compared with controls. Diffusion MRI data suggest reduced white matter organisation involving sensori-motor structures and altered structural connectivity across the whole brain network. Interpretation. Taken together, results support the hypothesis that children with DCD show differences in brain structure and function compared with typically developing children. Behaviourally, these differences may impact anticipatory planning and reduce automatization of movement skill, prompting greater reliance on slower feedback-based control and compensatory strategies. Implications for future research, theory development and clinical practice are discussed.