The effect of motor control exercise versus placebo in patients with chronic low back pain

Background: While one in ten Australians suffer from chronic low back pain this condition remains extremely difficult to treat. Many contemporary treatments are of unknown value. One potentially useful therapy is the use of motor control exercise. This therapy has a biologically plausible effect, is readily available in primary care and it is of modest cost. However, to date, the efficacy of motor control exercise has not been established. Methods: This paper describes the protocol for a clinical trial comparing the effects of motor control exercise versus placebo in the treatment of chronic non-specific low back pain. One hundred and fifty-four participants will be randomly allocated to receive an 8-week program of motor control exercise or placebo (detuned short wave and detuned ultrasound). Measures of outcomes will be obtained at follow-up appointments at 2, 6 and 12 months after randomisation. The primary outcomes are: pain, global perceived effect and patient-generated measure of disability at 2 months and recurrence at 12 months. Discussion: This trial will be the first placebo-controlled trial of motor control exercise. The results will inform best practice for treating chronic low back pain and prevent its occurrence.

How Can Models of Motor Control Be Useful for Understanding Low Back Pain?

Introduction. The purpose of this chapter is to address the question raised in the chapter title. Specifically, how can models of motor control help us understand low back pain (LBP)? There are several classes of models that have been used in the past for studying spinal loading, stability, and risk of injury (see Reeves and Cholewicki (2003) for a review of past modeling approaches), but for the purpose of this chapter we will focus primarily on models used to assess motor control and its effect on spine behavior. This chapter consists of 4 sections. The first section discusses why a shift in modeling approaches is needed to study motor control issues. We will argue that the current approach for studying the spine system is limited and not well-suited for assessing motor control issues related to spine function and dysfunction. The second section will explore how models can be used to gain insight into how the central nervous system (CNS) controls the spine. This segues segue nicely into the next section that will address how models of motor control can be used in the diagnosis and treatment of LBP. Finally, the last section will deal with the issue of model verification and validity. This issue is important since modelling accuracy is critical for obtaining useful insight into the behavior of the system being studied. This chapter is not intended to be a critical review of the literature, but instead intended to capture some of the discussion raised during the 2009 Spinal Control Symposium, with some elaboration on certain issues. Readers interested in more details are referred to the cited publications.

Trait and behavioural motor control is associated with resistance to overconsumption

While overall obesity rates are rising, a minority of individuals appear to resist overconsumption and remain lean in spite of an ‘obesogenic’ environment. Studying the factors hypothesised to underpin behaviours associated with resistance to overconsumption may inform weight management strategies in an adverse environment. Trait (BIS-11) and behavioural (response inhibition, GoStop) self control were assessed in the laboratory. Snack food consumption was measured covertly via a sham taste test. Lack of motor control was positively correlated (r = .32, p <. 05) and successful response inhibition was negatively correlated (r = −.35, p <. 05) with snack food intake. Low motor control was also associated with further food intake when satiated (r = .39, p < .01). These relationships were independent of self-reported palatability and perceived reward value of the food. Motor control may be an important factor implicated in ‘mindless’ eating in an environment abundant in palatable, energy-dense snack foods.

Computational approaches to motor control.

This review will focus on four areas of motor control which have recently been enriched both by neural network and control system models: motor planning, motor prediction, state estimation and motor learning. We will review the computational foundations of each of these concepts and present specific models which have been tested by psychophysical experiments. We will cover the topics of optimal control for motor planning, forward models for motor prediction, observer models of state estimation arid modular decomposition in motor learning. The aim of this review is to demonstrate how computational approaches, as well as proposing specific models, provide a theoretical framework to formalize the issues in motor control.

Motor control is decision-making.

Motor behavior may be viewed as a problem of maximizing the utility of movement outcome in the face of sensory, motor and task uncertainty. Viewed in this way, and allowing for the availability of prior knowledge in the form of a probability distribution over possible states of the world, the choice of a movement plan and strategy for motor control becomes an application of statistical decision theory. This point of view has proven successful in recent years in accounting for movement under risk, inferring the loss function used in motor tasks, and explaining motor behavior in a wide variety of circumstances.

Pain relativity in motor control.

Motivational theories of pain highlight its role in people's choices of actions that avoid bodily damage. By contrast, little is known regarding how pain influences action implementation. To explore this less-understood area, we conducted a study in which participants had to rapidly point to a target area to win money while avoiding an overlapping penalty area that would cause pain in their contralateral hand. We found that pain intensity and target-penalty proximity repelled participants' movement away from pain and that motor execution was influenced not by absolute pain magnitudes but by relative pain differences. Our results indicate that the magnitude and probability of pain have a precise role in guiding motor control and that representations of pain that guide action are, at least in part, relative rather than absolute. Additionally, our study shows that the implicit monetary valuation of pain, like many explicit valuations (e.g., patients' use of rating scales in medical contexts), is unstable, a finding that has implications for pain treatment in clinical contexts.