Seminar 4 –
RMIT University, Melbourne, Australia
Shaping up movement intervention research
This paper examines the status of movement intervention research in DCD and proposes an alternative approach. I start with a brief historical overview of past research, highlighting what we have learned about DCD through conventional treatment methodologies. Essentially, we know that most treatment regimes involving performance of functional skills under different task and instructional conditions result in mild-to-moderate effect sizes, with limited evidence for generalisation across skill domains. Thus, training effects tend to be task-specific. As well, since all such studies involve a level of mediated instruction, the suggestion is that cognitive-affective components of treatment are important to remediation. We also know that a process-oriented solution for DCD has remained elusive. Treatment effects for SI Training and kinaesthetic training, for example, are negligible across studies.
Following on from my earlier presentation at the 2nd ESRC Seminar on DCD, I argue that treatment studies need to be better informed by current models of motor control and development. Intervention needs to transcend some of the traditional assumptions of clinical theory and the information processing approach, both of which have dominated thinking for several decades. The level(s) at which intervention is directed will really depend on how sophisticated our guiding model of (atypical) motor development is. The model of choice should be theoretically-principled, acknowledge the interplay between mechanism and process, be sensitive to developmental processes of change, and flexible enough to cater for individual differences in presentation, learning style and progression. The systems approach correctly conceptualises movement as an embodied phenomenon, shuns the artificial distinction between cognitive and motor function, and supports a multi-level analysis of movement skill.
Task-specific approaches to training do, however, neglect top-down control of action and the specification of universal neuromotor constraints. The cognitive neuroscience perspective can fill this void by mapping (emerging) brain systems that support movement over the course of development. One of the aims of this approach is to identify immaturities in neurocognitive function that might constrain the development of movement skill. Interventions might then be developed to stimulate those (underlying) brain systems that show immaturity, encouraging appropriate integration or differentiation of processing. Using this approach, internal modelling of movement is one hypothesis our research group has developed to account for poor coordination in children.
This account was explained fully in the 2nd ESRC seminar, but here I describe two intervention studies using a movement imagery training protocol that provide preliminary support for this hypothesis. More broadly these data support the use of intervention directed at the level of neurocognitive function. I am quick to acknowledge that not all children with DCD manifest a deficit in movement imagery (our probe for internal modelling). Indeed, we see that around one-third of children with DCD manifest normal performance on imagery and other measures of internal modelling including double-step saccade task and covert orienting of attention.
I propose that a hybrid model that embraces principles both dynamic systems
theory and developmental cognitive neuroscientific can support a multi-level
approach to both assessment and treatment.
Multi-level assessment and treatment might involve three stages: (1) functional performance assessed against age norms, (2) movement strategies that reflect the interaction of environmental, biomechanical, and task factors, and (3) impairment (i.e., the integrity of supportive neurocognitive and affective systems). If children are achieving their movement goals at Level 1, then clearly intervention is not indicated. The approach to intervention at Level 2 would involve scaling task and environmental constraints up or down to facilitate goal achievement (much like a Ecological Task Analysis), together with more general motor learning strategies. If this input shows only modest improvement in the speed, efficiency, and functional integrity of movements, then Level 3 might be enlisted, with training directed at particular neurocognitive bases. Thus, assessment at multiple levels of function maps quite seamlessly to intervention.
I then consider specific ways of beefing up (intervention) research design and the precision of measurement tools. Certain caveats of good design of course apply equally well to DCD research. Among them, the choice of appropriate control groups/conditions is pivotal: controlling for treatment duration, the effect of the mere presence of an instructor, and methods of randomisation are important considerations here. Sub-group specific hypotheses will also help test what aspects of a training program are providing therapeutic benefit.
The effect of DCD severity and the presence of comorbid conditions are two
other important considerations that bear on subject selection and screening.
With respect to outcome measures, one unhelpful belief is that because a
movement assessment device is good at screening children for DCD, then it
also provides a precise measure of change through intervention. This is not
the case. For example, most researchers defer to the MABC for pre-post measurement
of change. While the MABC is a good diagnostic tool, unfortunately it uses
standardised impairment scores which create a highly truncated measure of
performance. Variation in ability is not well captured in the upper and lower
ranges for any age group. At the end of the day, we live or die by the precision
of our change measures. Truly continuous measures of performance should be
the number one criterion for selection, with sensitivity to age-related variation
being the second. I also suggest that multiple baseline measures are recommended
as a way of reducing the standard error of measurement in pre-post designs.
Depending on the scope of the hypothesis, direct intervention effects can be measured at a number of levels: functional skill, kinematic-kinetic, and neurocognitive. We also know from the mainstream developmental literature and systems theory that task performance is always a function of a dynamic interplay between Task, Environment, and Individual. At the level of the individual, a number of internal factors determine the extent to which a child is committed to a performance goal, how well they engage with a given learning situation, and their ability to explore and implement learning strategies: physiological constraints, affective state, motivation, and self-efficacy are important variables that can be measured using a variety of tools—subjective/psychological, neuropsychological, and behavioural. Thus, both the treatment cocktail and outcome measures need to be carefully selected (guided by theory) and measured in a valid and reliable way.
To say that there is much work to be done in the area of intervention research
is somewhat of an understatement. Product-oriented assessment and treatment
is fine but our research needs to be supported by more rigorous models of
behavioural development. A blending of constraint-based systems models and
developmental cognitive neuroscience can provide such a framework for DCD.
In the process, our design and measurement will become increasingly multi-level and multi-modal. Great sophistication in research design is then needed to test specific hypotheses. This is a worthy endeavour but one that requires great care, time, and patience.