Skip to main content
  • Other Publications
  • Subscribe
  • Contact Us
Advertisement
JCORE Reference
this is the JCORE Reference site slogan
  • Home
  • Most Read
  • About Us
    • About Us
    • Editorial Board
  • More
    • Advertising
    • Alerts
    • Feedback
    • Folders
    • Help
  • Patients
  • Reference Site Links
    • View Regions
  • Archive

Predicting Response to Motor Control Exercises and Graded Activity for Patients With Low Back Pain: Preplanned Secondary Analysis of a Randomized Controlled Trial

Luciana Gazzi Macedo, Christopher G. Maher, Mark J. Hancock, Steve J. Kamper, James H. McAuley, Tasha R. Stanton, Ryan Stafford, Paul W. Hodges
DOI: 10.2522/ptj.20140014 Published 1 November 2014
Luciana Gazzi Macedo
L.G. Macedo, PT, PhD, Physical Therapy, University of Alberta, 2-50 Corbett Hall, Edmonton, Alberta T6G 2G4, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christopher G. Maher
C.G. Maher, PT, PhD, The George Institute for Global Health, The University of Sydney, Sydney, New South Wales, Australia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mark J. Hancock
M.J. Hancock, PT, PhD, Discipline of Physiotherapy, Faculty of Human Sciences, Macquarie University, Sydney, New South Wales, Australia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Steve J. Kamper
S.J. Kamper, PT, PhD, EMGO+ Institute, VU University Medical Centre, Amsterdam, the Netherlands, and The George Institute for Global Health, The University of Sydney.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James H. McAuley
J.H. McAuley, PhD, Neuroscience Research Australia, Sydney, New South Wales, Australia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tasha R. Stanton
T.R. Stanton, PT, PhD, School of Health Sciences, The University of South Australia, Adelaide, South Australia, Australia, and Neuroscience Research Australia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ryan Stafford
R. Stafford, PhD, School of Health and Rehabilitation Sciences, The University of Queensland, Brisbane, Queensland, Australia.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Paul W. Hodges
P.W. Hodges, PT, PhD, Physiotherapy, School of Health and Rehabilitation Sciences, The University of Queensland.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Background Current treatments for low back pain have small effects. A research priority is to identify patient characteristics associated with larger effects for specific interventions.

Objective The aim of this study was to identify simple clinical characteristics of patients with chronic low back pain who would benefit more from either motor control exercises or graded activity.

Design This study was a secondary analysis of the results of a randomized controlled trial.

Methods One hundred seventy-two patients with chronic low back pain were enrolled in the trial, which was conducted in Australian physical therapy clinics. The treatment consisted of 12 initial exercise sessions over an 8-week period and booster sessions at 4 and 10 months following randomization. The putative effect modifiers (psychosocial features, physical activity level, walking tolerance, and self-reported signs of clinical instability) were measured at baseline. Measures of pain and function (both measured on a 0–10 scale) were taken at baseline and at 2, 6, and 12 months by a blinded assessor.

Results Self-reported clinical instability was a statistically significant and clinically important modifier of treatment response for 12-month function (interaction: 2.72; 95% confidence interval=1.39 to 4.06). Participants with high scores on the clinical instability questionnaire (≥9) did 0.76 points better with motor control exercises, whereas those who had low scores (<9) did 1.93 points better with graded activity. Most other effect modifiers investigated did not appear to be useful in identifying preferential response to exercise type.

Limitations The psychometric properties of the instability questionnaire have not been fully tested.

Conclusions A simple 15-item questionnaire of features considered indicative of clinical instability can identify patients who respond best to either motor control exercises or graded activity.

Randomized controlled trials and systematic reviews evaluating the effectiveness of interventions for patients with chronic, nonspecific low back pain (LBP) typically demonstrate small treatment effects.1,2 It has been proposed that it may be possible to identify patients who are more likely to respond to a specific treatment (compared with no treatment or an alternative treatment) and for whom treatment effects are larger.3,4 Investigating subgroups of patients with LBP with specific characteristics who respond best to different treatments has been identified as the number one research priority in this field.5,6

Exercise therapy is endorsed in guidelines7 and systematic reviews2 as an effective treatment for chronic LBP. However, although more effective than no intervention, the effect size of exercise, like other back pain treatments, is small. A meta-regression study8 investigated various aspects of exercise programs and identified that individually designed programs that included stretching or strengthening and that included supervision had larger treatment effects. To illustrate this result, the effect of exercise estimated from all 43 trials in the review was 3.4 (95% confidence interval [95% CI]=2, 4.7) points reduction in pain, measured on a 0–100 pain scale.8 However, the authors estimated that the effect would rise to 18.1 points (95% CI=11.1, 25.0) for programs including the most effective intervention characteristics. Although it is plausible that identification of characteristics of the patients who respond best to different types of exercise may further enhance the treatment effects, this possibility is yet to be investigated.

Motor control exercises (sometimes called lumbar stabilization exercises) and graded activity using the principles of cognitive-behavioral therapy are 2 popular forms of exercise therapy for people with chronic LBP, with evidence of effectiveness from randomized controlled trials9,10 and systematic reviews.11,12 Motor control exercises use a motor learning approach to optimize control of the spine and pelvis via rehabilitation of posture, movement, and the coordination of muscles involved in the control and movement of the spine.13 Therefore, this treatment is expected to work best in people who have impaired control and coordination of the spinal muscles, which have been proposed to include both reduced and excessive spinal stability.14,15 Graded activity uses a cognitive-behavioral approach to increase activity tolerance by addressing pain-related fear, kinesiophobia, and unhelpful beliefs and behaviors concerning back pain while correcting physical impairments such as impaired endurance, muscle strength, and balance.10 Theoretically, this treatment should work best in patients who are physically deconditioned and have unhelpful beliefs about their back pain. Given that both exercise interventions are based on specific rationales, plausible treatment effect modifiers related to characteristics of the patient can be explored. If characteristics of patients who respond best to one of these exercise interventions compared with the other can be identified, patient outcomes could be improved.

The aim of this study was to identify simple clinical characteristics of patients who would benefit more from motor control exercises compared with graded activity, or vice versa, by evaluating potential treatment effect modifiers, identified a priori based on each treatment rationale. Guidelines16,17 on evaluation of treatment effect modification and clinical prediction rules were followed to ensure high methodological quality.

Method

Design Overview

The data for this study were drawn from a randomized clinical trial18 comparing motor control exercises to graded activity for patients with chronic, nonspecific LBP. The trial was conducted in Sydney and Brisbane physical therapy clinics, with participants enrolled in the trial during the period October 2007 to November 2009. The trial, including effect modification analyses, was prospectively registered (ACTRN12607000432415) and the trial protocol published.19 All patients signed an informed consent form prior to their inclusion in the study.

Setting and Participants

Patients with LBP of greater than 3 months' duration were invited to participate if they met the following criteria: chronic, nonspecific LBP (>3 months' duration) with or without leg pain; currently seeking care for LBP; between 18 and 80 years of age; English speaker; suitable for active exercises (as assessed with the Physical Activity Readiness Questionnaire from the American College of Sports Medicine guidelines)20; expected to reside in the Sydney or Brisbane region for the study duration; and had a score of moderate or greater on question 7 (How much bodily pain have you had during the past week?) or 8 (During the past week, how much did pain interfere with your normal work, including both work outside the home and housework?”) of the 36-Item Short-Form Health Survey (SF-36).

Exclusion criteria were: known or suspected serious pathology, nerve root compromise (at least 2 signs of the same spinal nerve: sensation loss, reduced or absent reflexes or myotomal weakness), pregnancy, previous spinal surgery or scheduled for surgery during the trial; and contraindication to exercise program.

Randomization and Interventions

The randomization sequence with a 1:1 allocation ratio was computer-generated by an investigator not involved in recruitment or treatment allocation. Allocation codes were concealed in sequentially numbered, sealed, opaque envelopes by the same investigator who created the randomization sequence. The primary goal of the motor control exercise program was to enable the patient to regain control and coordination of the spine and pelvis using principles of motor learning.21 The intervention was based on assessment of the individual participant's trunk coordination (including consideration of muscle activation, posture, and movement) and treatment goals (set collaboratively with the therapist). The first stage of the intervention included the implementation of a protocol designed to improve the activation of muscles identified to have poor control, such as the transversus abdominis, multifidus, and pelvic-floor muscles,22 and reduce the activity of any muscles identified to be overactive, such as the obliquus externus abdominis muscle. The second stage included the progression of the exercises toward more functional activities using static and then dynamic tasks.23

The primary goal of the graded activity program was to increase activity tolerance by performing individualized and submaximal exercises. The program was based on the activities that each participant identified as problematic. The activities in the program were progressed in a time-contingent manner (rather than a pain-contingent manner) from the baseline-assessed ability to a target goal set jointly by participant and therapist. Participants received daily quotas and were instructed to perform the agreed-upon amount. Cognitive-behavioral principles were used to address negative behaviors and pain-related anxiety. Both programs are comprehensively described in the original publication, including a table delineating specific characteristics of each intervention.18

Baseline Predictors of Response

Baseline characteristics of each trial participant were collected by a researcher who was blinded to the participant's treatment allocation. Seven baseline characteristics that would plausibly predict preferential response to graded activity compared with motor control exercises were selected a priori and are presented in Table 1. The predicted direction of effect also was defined for each predictor.17

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table 1.

Description of Candidate Baseline Predictorsa

The 7 putative predictors were measures of walking tolerance, habitual physical activity, self-reported signs of clinical instability (Appendix), self-efficacy, coping strategies, fear and anxiety of pain, and psychosocial risk factors. We chose measures to evaluate the constructs based on ease of clinical application and ready availability. The predictors were prespecified in a published trial protocol19; however, some changes to the protocol were required. We replaced the Three-Minute Step Test with the Shuttle Walk Test based on feasibility testing prior to starting the trial. The laboratory measures of trunk proprioception, trunk stiffness, trunk muscle response, and deep muscle control were not included in this analysis, as these complex neurophysiological measures cannot be performed in a typical clinic and, therefore, did not align with the aim of this study to identify simple clinical characteristics of patients who would benefit more from motor control exercises or graded activity. The complex neurophysiological measures were only collected in a subset of patients (n=76) and will be used in a further study investigating mechanisms. The instruments used in the current study, and their interpretation, are summarized in Table 1.

Our hypothesis was that graded activity would be superior to motor control exercises in participants with low walking tolerance, low habitual physical activity, low self-reported clinical instability, low self-efficacy, low coping, high fear and anxiety, and high psychosocial risk and that motor control exercises would be superior to graded activity in participants with high self-reported instability.

Outcome Measures and Follow-up

Measurements of pain and function were taken at baseline and at 2, 6, and 12 months by a blinded assessor. Pain was measured as the average pain over the previous week using a 0–10 scale (low scores indicate less pain), and function was measured using the 0–10 Patient-Specific Functional Scale (PSFS) (high scores indicate greater function).21 We chose the PSFS because it is more responsive than other measures such as the Roland-Morris Disability Questionnaire.21

Data Analysis

We prespecified a threshold of 2 units (∼1.0 standard deviation) for a clinically important interaction effect for both outcomes.19 The sample size of 172 participants was calculated a priori to detect an interaction effect size of 1.0 standard deviation and a treatment main effect of 0.5 standard deviation, with an alpha level of .05 and power of 0.80 and allowing for 10% loss to follow-up and 10% treatment nonadherence.19 An intention-to-treat method was used in all statistical analyses.

We investigated baseline patient characteristics associated with a greater effect of graded activity versus motor control exercises for the primary trial outcomes of pain and function at 2 and 12 months (ie, separate models for each of these 2 follow-ups). We did not analyze response to treatment at the 6-month follow-up in order to decrease the number of models and, therefore, the chance of type I error. Outcomes at 2 and 12 months represent short-term and long-term follow-ups. We began by investigating individual factors, but we also investigated combinations of factors. Treatment effect modification was evaluated using a group × predictor interaction term.17 The models were built using the linear regression model commands within IBM SPSS Statistics version 21 (IBM Corp, Armonk, New York).

Univariate testing.

As the goal was to identify clinical subgroups that could be simply identified, we dichotomized the predictors using a median split and then built separate models to predict pain and function outcomes at 2 months and 12 months for the 7 predictors. The models included terms for patient group, predictor, group × predictor interaction, and baseline score for the dependent variable. Predictors that provided a P value <.20 for the group × predictor term proceeded to the multivariate testing. A median split was used to dichotomize the predictors. We did not perform analyses to choose an “optimal” cutoff point, as this approach is strongly advised against.22

Multivariate modeling.

As we also were interested in building a clinical prediction rule, we attempted to build a multivariate model. We used a backward selection procedure to build the models. We entered all predictors from the univariate models with a P value <.20 into the first multivariate model and in subsequent models removed one predictor at a time starting with the predictor with the highest P value until only predictors with a P value <.05 remained.

Role of the Funding Source

The trial received funding from Australia's National Health and Medical Research Council.

Results

Participant flow through the study is shown in Figure 1, and the baseline characteristics of the participants are shown in Table 2.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Study flow diagram. IQR=interquartile range.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table 2.

Baseline Characteristics of Participantsa

Univariate Testing

The results of the univariate testing are shown in Table 3. The Lumbar Spine Instability Questionnaire (LSIQ), Coping Strategies Questionnaire, Pain Anxiety Symptom Scale, and Örebro Low Back Pain Screening Questionnaire were found to be statistically significant (P<.05) treatment effect modifiers for function at 12 months but not at 2 months. For example, the effect of graded activity versus motor control exercises was greater in participants with low instability (based on LSIQ scores); the mean point estimate for the interaction was 2.72 (95% CI=1.39, 4.06) units on the 0–10 function scale. The other 3 significant interaction effects favored graded activity over motor control exercises in participants with low coping (based on Coping Strategies Questionnaire scores), low fear (based on Pain Anxiety Symptom Scale scores), and low psychosocial risk (based on Örebro questionnaire scores) but did not reach our prespecified threshold for an interaction of 2 units. Additionally, 2 predictors (fear and psychosocial risk) did not influence outcomes in the hypothesized direction. The adjusted treatment effects in subgroups that were positive and negative on each statistically significant treatment effect modifier are shown in Table 4.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table 3.

Results of Univariate Testing of the Dichotomized Predictor Variables on Function Scoresa

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table 4.

Adjusted Function (Patient-Specific Functional Scale) Treatment Effects (95% Confidence Interval) in Subgroup Positive and Subgroup Negative Participants for the Statistically Significant Predictors Onlya

To illustrate the effect of self-reported signs of instability on treatment effect, Figure 2 shows outcomes in both treatment groups at baseline and 2- and 12-month follow-ups for all participants and in a separate panel with the groups stratified using the median LSIQ score of 9. Participants with an LSIQ score of 9 or greater (ie, high instability) are described as “positive” and those with an LSIQ score of less than 9 are described as “negative” on the questionnaire. At 12 months, participants who were positive on the LSIQ did 0.76 points better with motor control exercises than with graded activity, whereas those who were negative on the LSIQ did 1.93 points better with graded activity than with motor control exercises. These findings mean that on a scale from 0 to 10, where 0 is low function and 10 is high function, an individual who did not have instability and received graded activity was about 2 points more functional a year after inclusion in the study than those who did not have instability and received motor control exercises. This is a large difference that has been reported to be clinically significant.23

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Function outcomes at baseline and 12-month follow-up to illustrate the main effect of treatment and treatment effect modification. Values represent unadjusted means and 95% confidence intervals. Graph A shows data for all participants. Graph B shows the outcome when the groups were stratified by median score on the Lumbar Spine Instability Questionnaire (LSIQ). Participants with an LSIQ score of 9 or greater (ie, high instability) are described as “positive” (+ve), and those with an LSIQ score of less than 9 are described as “negative” (−ve) on the questionnaire.

Multivariate Modeling

The LSIQ, Coping Strategies Questionnaire, Pain Anxiety Symptom Scale, and Örebro questionnaire yielded P values <.20 for predicting function at 12 months, and the Coping Strategies Questionnaire, Pain Anxiety Symptom Scale, and Örebro questionnaire yielded P values <.20 for predicting pain at 12 months. These became candidate variables for the multivariate analysis. None of the predictors achieved P values <.20 for short-term outcomes.

We were unable to build a multivariate model for pain or function outcomes at 12 months. The final pain model included the Örebro questionnaire, which did not achieve a P value <.05. The final function model included the LSIQ, which did achieve a P value <.05.

Discussion

Statement of Principal Findings

We found that motor control exercises provided better function outcomes at 12 months than graded activity in patients with self-reported signs of clinical instability (LSIQ score <9), but in those who scored low on the questionnaire of clinical instability (LSIQ score ≥9), the situation was reversed and graded activity provided better function outcomes. This finding is consistent with the theoretical rationale for motor control training. The treatment effect modification was statistically significant and larger than the threshold of 2 units for a clinically important interaction effect we prespecified in the published trial protocol.19 Measures of coping, fear and anxiety, and psychosocial risk also moderated the effect of treatment on function at 12 months but did not reach our prespecified threshold. There were no statistically significant interactions for pain at 2 and 12 months or for function at 2 months.

Strengths and Weaknesses of the Study

The strengths of the study are that we tested effect modification in a high-quality trial, and we followed a prespecified protocol. We investigated a limited number of prespecified predictors underpinned by theory. The analysis used appropriately constructed interaction terms, and we blinded assessors of outcome to predictors and group allocation. One of the potential problems with evaluating treatment effect modification is a high type I error rate associated with repeated testing. To minimize this effect, we undertook a stepped approach. Nevertheless, we acknowledge that we have taken a fairly exploratory approach and that any positive results will need replication in an independent data set. Our view is that the results of this study should be viewed cautiously, and it would be premature to advocate clinical application at this stage. We also would caution that the LSIQ was developed from the results of a Delphi study of experienced clinicians aiming to identify features associated with instability.

Self-administration of the LSIQ required adjustment of some features. For instance, the consensus feature “Reports feelings of giving way or back giving out” became item 1: “I feel like my back is going to give way or give out on me.” We performed post hoc evaluation of the internal consistency and the influence of floor and ceiling effects for the LSIQ in our sample. Cronbach's alpha was calculated as a measure of internal consistency and interpreted according to the threshold provided by de Vet et al,24 and the threshold proposed by McHorney and Tarlov25 was used to determine the presence of floor or ceiling effects. Cronbach's alpha for the LSIQ was .69 (95% CI=.62, .76), which falls marginally below the lower bound of the acceptable range of .7 to .9 proposed by de Vet et al.24 The distribution of scores on the scale showed that neither floor nor ceiling effects are of concern. As only 1 participant (0.6%) reported the maximum score on the scale and no participants reported the minimum score, these findings fall well below the threshold of 15% of the sample at each end-point.25 Future comprehensive evaluation of the psychometric properties and interpretation of the questionnaire are needed.

Strengths and Weaknesses in Relation to Other Studies

Although numerous studies have attempted to identify subgroups of responders to a specific treatment for LBP, almost all are poorly designed, and no previous randomized trials have investigated subgroups of responders to different exercise approaches.26 Arguably, the best study investigating a subgroup of responders to a specific treatment for LBP is the study of Childs and colleagues,27 who developed a rule to identify patients with LBP who respond best to spinal manipulation treatment. Although these authors expressed effect modification in a slightly different way from that used in our study, it is possible to obtain equivalent data from interpolation of the figures in the article. Treatment effect modification was approximately 25 units on the 0–100 Oswestry Low Back Pain Disability Questionnaire at 1 week, which is similar in magnitude to the effect we observed on function.

Meaning of the Study: Implications for Clinicians and Policy Makers

Although it is essential to use interaction terms to test treatment subgroups, the interaction term itself does not describe the treatment effect within the group but rather the difference between the treatment effect in patients meeting the subgroup criteria and those who do not. What we can determine is that people with a score of 9 or greater on the LSIQ (clinical instability) did 0.76 points (Fig. 1) better with motor control exercises, whereas people who had low scores for the LSIQ (<9) did 1.93 points better with graded activity. At 12 months, the treatment effect in the negative subgroup (−1.93; 95% CI=−3.00, −0.85) was statistically and clinically significant, implying graded activity was clearly superior to motor control exercises in these patients. The treatment effect in the positive subgroup was smaller and not statistically significant (0.76; 95% CI=−0.07, 1.58). It is essential to note that this study was comparing 2 effective interventions.11,12,18 Therefore, an additional benefit of 0.76 points, by selecting motor control exercises over graded activity in these patients, is considered clinically important by the authors, especially considering the interventions have similar costs and potential harms. The 95% CI values crossed zero likely due to lack of power, and larger trials are needed in the future to validate the finding that people who score positively on the LSIQ have slightly better outcomes with motor control exercises compared with graded activity. Using the LSIQ score to contribute to decision making between graded activity and motor control exercises appears to have little downside, as both treatments are effective and carry few risks. However, as is always the case, it is important to consider other factors, such as patient preference and clinician expertise, while making treatment decisions and not rely solely on LSIQ score. This appears to be the case particularly in people with positive LSIQ scores, where the benefits of choosing motor control exercises over graded activity are relatively small.

As the current trial did not have a no-treatment control group, it is not possible to determine the effect of either intervention compared with no treatment. However, the unadjusted mean (95% CI) improvement in function from baseline in people who received graded activity and had low scores on the LSIQ was 3.7 (95% CI=2.8, 4.5), whereas the improvement was less than half this (1.8; 95% CI=1.1, 2.5) in those who received graded activity and had high scores on the LSIQ. In those patients who received motor control exercises, the improvement was 2.4 (95% CI=1.7, 3.0) in those who scored high on the LSIQ and 1.7 (95% CI=0.7, 2.7) in those who scored low on the LSIQ. If the results of the current study can be replicated, they are a major breakthrough and have important implications for management of chronic LBP. The results suggest that by targeting the right patients (those with or without clinical instability) to these 2 common exercise approaches, we may have a simple, relatively cheap method to increase the effectiveness of these treatments for patients with chronic LBP. Implementation of this approach would be very simple, as both treatments are already widely used, and the method to identify subgroups of responders to each approach is very simple.

Unanswered Questions and Future Research

An interesting finding from our study is that the interaction effect was not statistically significant for function at 2 months, although the mean estimate (0.82) suggests that at this early time point, the scores on the LSIQ were already associated with response to exercise type. This finding suggests our study was not powered to identify these smaller early effects. Larger trials in the future should provide adequate power to assess the importance of the LSIQ score to early response to graded exercise or motor control exercises. However, in patients with chronic LBP, long-term outcomes are widely considered most important. We did not find a statistically significant interaction effect for the LSIQ on pain outcomes at 12 months; however, the estimate of −0.96 (95% CI=−2.59, 0.67) again suggests our study was not powered to find these smaller effects. We used a median split to dichotomize the LSIQ and suggest the same cutoff point (ie, >9) be used in future validation studies; however, exploration of different cutoff points also may be valuable. The current trial investigated only people with chronic LBP, and it is not clear whether the findings would generalize to those with acute LBP. It is in people with chronic LBP that exercise is more widely recommended; however, the findings of the current study indicate the possibility of better effects of exercise in patients with acute or subacute LBP if better matched to the patient's presentation. Future research is needed to investigate this possibility.

The Bottom Line

What do we already know about this topic?

Motor control exercise and graded activity are two forms of exercise intervention for chronic low back pain. Both interventions are known to be effective; however, clinicians lack a method to help choose one option over the other for specific patients.

What new information does this study offer?

The results of this study demonstrated that a simple 15-item questionnaire on clinical instability can help identify patients with chronic low back pain who respond best to either motor control or graded activity exercises. Replication in future studies is required.

If you're a patient, what might these findings mean for you?

A simple questionnaire may help clinicians choose the best type of exercise for individual patients with low back pain, which might help patients achieve better outcomes.

Appendix.

Appendix.
  • Download figure
  • Open in new tab
  • Download powerpoint
Appendix.

Lumbar Spine Instability Questionnaire

Footnotes

  • All authors provided concept/idea/research design. Dr Macedo, Dr Maher, Dr Hancock, Dr Kamper, Dr McAuley, Dr Stanton, and Dr Hodges provided writing. Dr Macedo, Dr McAuley, Dr Stanton, Dr Stafford, and Dr Hodges provided data collection. Dr Macedo, Dr Maher, Dr Kamper, Dr McAuley, and Dr Hodges provided data analysis. Dr Macedo and Dr Stafford provided project management. Dr Hodges and Dr Maher provided fund procurement. Dr Macedo, Dr Maher, Dr Hancock, Dr Kamper, Dr McAuley, Dr Stanton, and Dr Hodges provided consultation (including review of manuscript before submission). The funders had no role in the study, and there are no conflicts of interest.

  • The study was funded by the National Health and Medical Research Council. Dr Macedo is supported by the Canadian Institutes of Health Research and the Alberta Innovates Health Solutions. Prof Maher is supported by an Australian Research Council Fellowship. Dr Kamper is supported by an NHMRC fellowship. Dr Stanton is supported by the Canadian Institutes of Health Research Postdoctoral Training Fellowship [ID 223354]. Prof Hodges is supported by a Senior Principal Research Fellowship from the NHMRC (APP1002190).

  • The trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000432415).

  • Received January 21, 2014.
  • Accepted June 28, 2014.
  • © 2014 American Physical Therapy Association

References

  1. ↵
    1. Machado LA,
    2. Maher CG,
    3. Herbert RD,
    4. et al
    . The effectiveness of the McKenzie method in addition to first-line care for acute low back pain: a randomized controlled trial. BMC Med. 2010;8:10.
    OpenUrlCrossRefPubMed
  2. ↵
    1. Hayden JA,
    2. van Tulder MW,
    3. Malmivaara AV,
    4. Koes BW
    . Meta-analysis: exercise therapy for nonspecific low back pain. Ann Intern Med. 2005;142:765–775.
    OpenUrlCrossRefPubMedWeb of Science
  3. ↵
    1. Whitman JM,
    2. Cleland J,
    3. Mintken P
    . Clinical prediction rules in physical therapy: coming of age? J Orthop Sports Phys Ther. 2009;39:231–233.
    OpenUrlPubMed
  4. ↵
    1. Fritz JM
    . Clinical prediction rules in physical therapy: coming of age? J Orthop Sports Phys Ther. 2009;39:159–161.
    OpenUrlCrossRefPubMedWeb of Science
  5. ↵
    Low back pain research priorities: the view of the primary care practitioner. Paper presented at: Amsterdam International Forum VIII: Primary Care Research on Low Back Pain; June 8–10, 2006; Amsterdam, the Netherlands.
  6. ↵
    1. Costa Lda C,
    2. Koes BW,
    3. Pransky G,
    4. et al
    . Primary care research priorities in low back pain: an update. Spine (Phila Pa 1976). 2013;38:148–156.
    OpenUrlCrossRef
  7. ↵
    1. Chou R,
    2. Huffman LH
    . Nonpharmacologic therapies for acute and chronic low back pain: a review of the evidence for an American Pain Society/American College of Physicians clinical practice guideline. Ann Intern Med. 2007;147:492–504.
    OpenUrlCrossRefPubMedWeb of Science
  8. ↵
    1. Hayden JA,
    2. van Tulder MW,
    3. Tomlinson G
    . Systematic review: strategies for using exercise therapy to improve outcomes in chronic low back pain. Ann Intern Med. 2005;142:776–785.
    OpenUrlCrossRefPubMedWeb of Science
  9. ↵
    1. Costa LO,
    2. Maher CG,
    3. Latimer J,
    4. et al
    . Motor control exercise for chronic low back pain: a randomized placebo-controlled trial. Phys Ther. 2009;89:1275–1286.
    OpenUrlAbstract/FREE Full Text
  10. ↵
    1. Pengel LHM,
    2. Refshauge KM,
    3. Maher CG,
    4. et al
    . Physiotherapist-directed exercise, advice, or both for subacute low back pain: a randomized trial. Ann Intern Med. 2007;146:787–796.
    OpenUrlCrossRefPubMedWeb of Science
  11. ↵
    1. Macedo LG,
    2. Maher CG,
    3. Latimer J,
    4. McAuley JH
    . Motor control exercise for persistent, nonspecific low back pain: a systematic review. Phys Ther. 2009;89:9–25.
    OpenUrlAbstract/FREE Full Text
  12. ↵
    1. Macedo LG,
    2. Smeets R,
    3. Maher CG,
    4. et al
    . Graded activity and graded exposure for persistent non-specific low back pain: a systematic review. Phys Ther. 2010;90:860–879.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    1. Richardson CA,
    2. Jull GA,
    3. Hodges PW,
    4. Hides J
    . Therapeutic Exercise for Lumbopelvic Stabilization. A Motor Control Approach for the Treatment and Prevention of Low Back Pain. 2nd ed. Edinburgh, Scotland: Churchill Livingstone; 2004.
  14. ↵
    1. Hodges PW,
    2. Tucker K
    . Moving differently in pain: a new theory to explain the adaptation to pain. Pain. 2011;152(3 suppl):S90–S98.
    OpenUrlCrossRefPubMedWeb of Science
  15. ↵
    1. Hodges PW,
    2. Coppieters MW,
    3. MacDonald D,
    4. Cholewicki J
    . New insight into motor adaptation to pain revealed by a combination of modelling and empirical approaches. Eur J Pain. 2013;17:1138–1146.
    OpenUrlCrossRefPubMedWeb of Science
  16. ↵
    1. Hancock MJ,
    2. Herbert RD,
    3. Maher CG
    . Clinical guide to interpretation of studies investigating subgroups of responders to physiotherapy interventions. Phys Ther. 2009;89:698–704.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    1. Sun X,
    2. Briel M,
    3. Walter SD,
    4. Guyatt GH
    . Is a subgroup effect believable? Updating criteria to evaluate the credibility of subgroup analyses. BMJ. 2010;340:c117.
    OpenUrlFREE Full Text
  18. ↵
    1. Macedo LG,
    2. Latimer J,
    3. Maher CG,
    4. et al
    . Effect of motor control exercises versus graded activity in patients with chronic nonspecific low back pain: a randomized controlled trial. Phys Ther. 2012;92:363–377.
    OpenUrlAbstract/FREE Full Text
  19. ↵
    1. Macedo LG,
    2. Latimer J,
    3. Maher CG,
    4. et al
    . Motor control or graded activity exercises for chronic low back pain? A randomised controlled trial. BMC Musculoskelet Disord. 2008;9:65.
    OpenUrlCrossRefPubMed
  20. ↵
    1. Dwyer GB,
    2. Davis SE
    , eds; for the American College of Sports Medicine. ACSM's Health-Related Physical Fitness Assessment Manual. Philadelphia, PA: Lippincott Williams & Wilkins; 2005.
  21. ↵
    1. Pengel LH,
    2. Refshauge KM,
    3. Maher CG
    . Responsiveness of pain, disability, and physical impairment outcomes in patients with low back pain. Spine (Phila Pa 1976). 2004;29:879–883.
    OpenUrlCrossRef
  22. ↵
    1. Altman DG,
    2. Royson P
    . The cost of dichotomising continuous variables. BMJ. 2006;332:1080.
    OpenUrlFREE Full Text
  23. ↵
    1. Ostelo RW,
    2. Deyo RA,
    3. Stratford PW,
    4. et al
    . Interpreting change scores for pain and functional status in low back pain: towards international consensus regarding minimal important change. Spine (Phila Pa 1976) 2008;33:90–94.
    OpenUrlCrossRef
  24. ↵
    1. de Vet H,
    2. Terwee C,
    3. Mokkink L,
    4. Knol D
    . Measurement in Medicine. Cambridge, United Kingdom: Cambridge University Press; 2011.
  25. ↵
    1. McHorney CA,
    2. Tarlov AR
    . Individual-patient monitoring in clinical practice: are available health status surveys adequate? Qual Life Res. 1995;4:293–307.
    OpenUrlCrossRefPubMedWeb of Science
  26. ↵
    1. Stanton TR,
    2. Hancock MJ,
    3. Maher CG,
    4. Koes B
    . Critical appraisal of clinical prediction rules that aim to select treatments for musculoskeletal conditions. Phys Ther. 2010;90:843–854.
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Childs JD,
    2. Fritz JM,
    3. Flynn TW,
    4. et al
    . A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141:920–928.
    OpenUrlCrossRefPubMedWeb of Science
    1. Singh SJ,
    2. Morgan MD,
    3. Scott S,
    4. et al
    . Development of a shuttle walking test of disability in patients with chronic airways obstruction. Thorax. 1992;47:1019–1024.
    OpenUrlAbstract/FREE Full Text
    1. van Bloemendaal M,
    2. Kokkeler AM,
    3. van de Port IG
    . The Shuttle Walk Test: a new approach to functional walking capacity measurements for patients after stroke? Arch Phys Med Rehabil. 2012;93:163–166.
    OpenUrlCrossRefPubMed
    1. Campo LA,
    2. Chilingaryan G,
    3. Berg K,
    4. et al
    . Validity and reliability of the modified Shuttle Walk Test in patients with COPD. Arch Phys Med Rehabil. 2006;87:918–922.
    OpenUrlCrossRefPubMed
    1. Witham MD,
    2. Sugden JA,
    3. Sumukadas D,
    4. et al
    . A comparison of the Endurance Shuttle Walk Test and the Six Minute Walk Test for assessment of exercise capacity in older people. Aging Clin Exp Res. 2012;24:176–180.
    OpenUrlPubMed
    1. Craig CL,
    2. Marshall AL,
    3. Sjostrom M,
    4. et al
    . International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–1395.
    OpenUrlCrossRefPubMedWeb of Science
    1. Cook C,
    2. Brismee JM,
    3. Sizer PS Jr
    . Subjective and objective descriptors of clinical lumbar spine instability: a Delphi study. Man Ther. 2006;11:11–21.
    OpenUrlCrossRefPubMedWeb of Science
    1. Nicholas MK
    . The Pain Self-Efficacy Questionnaire: taking pain into account. Eur J Pain. 2007;11:153–163.
    OpenUrlCrossRefPubMedWeb of Science
    1. Kaivanto KK,
    2. Estlander AM,
    3. Moneta GB,
    4. Vanharanta H
    . Isokinetic performance in low back pain patients: the predictive power of the Self-Efficacy Scale. J Occup Rehabil. 1995;5:87–99.
    OpenUrlCrossRefPubMed
    1. Di Pietro F,
    2. Catley MJ,
    3. McAuley JH,
    4. et al
    . Rash analysis supports the use of the Pain Self-Efficacy Questionnaire. Phys Ther. 2014;94:91–100.
    OpenUrlAbstract/FREE Full Text
    1. Lawson K,
    2. Reesor KA,
    3. Keefe FJ,
    4. Turner JA
    . Dimensions of pain-related cognitive coping: cross-validation of the factor structure of the Coping Strategy Questionnaire. Pain. 1990;43:195–204.
    OpenUrlCrossRefPubMedWeb of Science
    1. Truchon M,
    2. Cote D
    . Predictive validity of the chronic pain coping inventory in subacute low back pain. Pain. 2005;116:205–212.
    OpenUrlCrossRefPubMedWeb of Science
    1. Riddle DL,
    2. Jensen MP
    . Construct and criterion-based validity of brief pain coping scales in persons with chronic knee osteoarthritis pain. Pain Med. 2013;14:265–275.
    OpenUrlCrossRefPubMedWeb of Science
    1. McCracken LM,
    2. Dhingra L
    . A short version of the Pain Anxiety Symptoms Scale (PASS-20): preliminary development and validity. Pain Res Manag. 2002;7:45–50.
    OpenUrlPubMed
    1. Linton SJ,
    2. Hallden K
    . Can we screen for problematic back pain? A screening questionnaire for predicting outcome in acute and subacute back pain. Clin J Pain. 1998;14:209–215.
    OpenUrlCrossRefPubMedWeb of Science
    1. Opsommer E,
    2. Hilfiker R,
    3. Raval-Roland B,
    4. et al
    . Test-retest reliability of the Örebro Musculoskeletal Pain Screening Questionnaire and the Situational Pain Scale in patients with chronic low back pain. Swiss Med Wkly. 2013;143:W13903.
    OpenUrlPubMed
    1. Dagfinrud H,
    2. Storheim K,
    3. Magnussen LH,
    4. et al
    . The predictive validity of the Örebro Musculoskeletal Pain Questionnaire and the clinician's prognostic assessment following manual therapy treatment of patients with LBP and neck pain. Man Ther. 2013;18:124–129.
    OpenUrlCrossRefPubMed
    1. Hockings RL,
    2. McAuley JH,
    3. Maher CG
    . A systematic review of the predictive ability of the Örebro Musculoskeletal Pain Questionnaire. Spine (Phila Pa 1976). 2008;33:E494–E500.
    OpenUrlCrossRef
View Abstract
PreviousNext
Back to top
Vol 94 Issue 11 Table of Contents
Physical Therapy: 94 (11)

Issue highlights

  • Response to Motor Control Exercises and Graded Activity for Patients With Low Back Pain
  • Task-Specific Training in Huntington Disease
  • Rehabilitation Therapies After Botulinum Toxin-A
  • Relationship Between Cumulative Lifting Load and Lumbar Disk Degeneration
  • Minimal Clinically Important Difference of the Functional Gait Index
  • Self-efficacy and Mobility With Wheelchair Use
  • KOOS-PS and KOOS Function and Sport Scores
  • Comparison of Ultrasound and Fingerbreadth Palpation Methods
  • Validation of the BESTest in Stroke
  • Valid Test for Manual Dexterity in Multiple Sclerosis
  • Introduction to the GRADE Approach
  • Theoretical Domains Framework
Email

Thank you for your interest in spreading the word on JCORE Reference.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Predicting Response to Motor Control Exercises and Graded Activity for Patients With Low Back Pain: Preplanned Secondary Analysis of a Randomized Controlled Trial
(Your Name) has sent you a message from JCORE Reference
(Your Name) thought you would like to see the JCORE Reference web site.
Print
Predicting Response to Motor Control Exercises and Graded Activity for Patients With Low Back Pain: Preplanned Secondary Analysis of a Randomized Controlled Trial
Luciana Gazzi Macedo, Christopher G. Maher, Mark J. Hancock, Steve J. Kamper, James H. McAuley, Tasha R. Stanton, Ryan Stafford, Paul W. Hodges
Physical Therapy Nov 2014, 94 (11) 1543-1554; DOI: 10.2522/ptj.20140014

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Download Powerpoint
Save to my folders

Share
Predicting Response to Motor Control Exercises and Graded Activity for Patients With Low Back Pain: Preplanned Secondary Analysis of a Randomized Controlled Trial
Luciana Gazzi Macedo, Christopher G. Maher, Mark J. Hancock, Steve J. Kamper, James H. McAuley, Tasha R. Stanton, Ryan Stafford, Paul W. Hodges
Physical Therapy Nov 2014, 94 (11) 1543-1554; DOI: 10.2522/ptj.20140014
del.icio.us logo Digg logo Reddit logo Technorati logo Twitter logo CiteULike logo Connotea logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
  • Article
    • Abstract
    • Method
    • Results
    • Discussion
    • Appendix.
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • Reliability and Validity of Force Platform Measures of Balance Impairment in Individuals With Parkinson Disease
  • Predictors of Reduced Frequency of Physical Activity 3 Months After Injury: Findings From the Prospective Outcomes of Injury Study
  • Effects of Locomotor Exercise Intensity on Gait Performance in Individuals With Incomplete Spinal Cord Injury
Show more Research Reports

Subjects

Footer Menu 1

  • menu 1 item 1
  • menu 1 item 2
  • menu 1 item 3
  • menu 1 item 4

Footer Menu 2

  • menu 2 item 1
  • menu 2 item 2
  • menu 2 item 3
  • menu 2 item 4

Footer Menu 3

  • menu 3 item 1
  • menu 3 item 2
  • menu 3 item 3
  • menu 3 item 4

Footer Menu 4

  • menu 4 item 1
  • menu 4 item 2
  • menu 4 item 3
  • menu 4 item 4
footer second
footer first
Copyright © 2013 The HighWire JCore Reference Site | Print ISSN: 0123-4567 | Online ISSN: 1123-4567
advertisement bottom
Advertisement Top