STUDY DESIGN: Clinical measurement. OBJECTIVES: To determine the interrater and intrarater reliability of the active hip abduction (AHAbd) test. BACKGROUND: The AHAbd test is used to assess lumbopelvic movement during a dynamic lower limb activity. The test has previously been shown to predict low back pain development during a prolonged standing exposure in previously asymptomatic individuals. As an observation-based assessment for which rater reliability has not been established, similar scoring on the test between clinicians is essential. METHODS: One hundred twenty-eight video clips of participants performing the AHAbd test were recorded. Sixteen practicing physical therapists scored test performance by viewing 20 preselected videos to establish interrater reliability. Fourteen of the 16 raters rescored the videos after a 3-week period to establish intrarater reliability. Demographic data were collected for all raters. Intraclass correlation coefficients (ICCs) were calculated for reliability statistics. Correlations were performed between demographic data and ICCs. RESULTS: Interrater reliability (ICC_2,1) for the test using the 4-point scale was 0.70 (95% confidence interval [CI]: 0.56, 0.84) and 0.59 (95% CI: 0.43, 0.76) when the scale was dichotomized into positive/negative scores. Intrarater reliability (ICC_3,1) was 0.74 on average. Demographic characteristics were not significantly associated with reliability scores. CONCLUSION: Interrater and intrarater reliability for scoring of the AHAbd test by practicing clinicians was similar, regardless of experience level or practice setting. The AHAbd test can be considered to be a reliable observational tool.

J Orthop Sports Phys Ther 2011;41(12):953-960, Epub 25 October 2011. doi:10.2519/jospt.2011.3684

KEY WORDS: low back pain, lumbar region, lumbopelvic control, stabilization

STUDY DESIGN: Analytic observational prospective study performed in a controlled laboratory setting. OBJECTIVES: To assess the ability of a new screening tool, the active hip abduction test, to predict low back pain development during prolonged standing in previously asymptomatic individuals. BACKGROUND: Most screening tools used for a patient with low back pain do not assess the patient’s ability to maintain postural control in the frontal plane, when placed in an unstable position. Postural-control differences in pain developers, as compared to non-pain developers, during standing have been found previously. An attempt was made to predict pain development with a simple screening test. METHODS: Forty-three previously asymptomatic volunteers underwent a clinical assessment prior to a 2-hour standing protocol designed to induce low back pain. Participants rated low back pain with a visual analog scale and were classified into pain developers or non-pain developers. RESULTS: Forty percent of participants developed low back pain. The active hip abduction test was the only test that discriminated between pain-developer groups. When the examiner scored the test, the odds ratio was 3.85 (95% confidence interval [CI]: 1.05-19.07), and when the test was self-rated, the odds ratio was 6.55 (95% CI: 1.14-37.75) for pain development during standing. CONCLUSION: The active hip abduction test appears to show promise for predicting individuals who are at risk for low back pain development during prolonged standing. More work is required to validate the test in clinical populations, and to assess interrater and intrarater reliability. LEVEL OF EVIDENCE: Diagnosis, level 2b.

J Orthop Sports Phys Ther 2009;39(9):649-657, Epub 24 June 2009. doi:10.2519/jospt.2009.3093

KEY WORDS: clinical assessment, diagnostic tests, lumbar spine, stabilization

STUDY DESIGN: Technical note. OBJECTIVES: To provide background theory and information and to describe relevant applications of autocorrelation and cross-correlation methodology as they apply to the field of motor control in human movement and rehabilitation research. BACKGROUND: Commonly used methodologies for pattern and event recognition, determination of muscle activation timing for investigation of movement coordination, and motor control are generally difficult to implement, particularly with large datasets. A brief description of the underlying mathematical theory of correlation analyses is given, followed by 4 different examples of how this methodology is useful for research in the movement sciences. METHODS: Examples demonstrating the utility of correlation analyses are presented from several different studies conducted at the University of Waterloo. RESULTS: Autocorrelation was used to demonstrate the presence of 60-Hz noise in anelectromyography signal that was not visible in the raw data. A "top-down" paraspinal muscle activation pattern was demonstrated for healthy adults during gait, with the use of cross-correlation. Cross-correlation was also used to quantify coactivation of bilateral gluteus medius muscles during standing in individuals who developed low-back pain. Gender differences in gluteus medius control of mediolateral center of pressure were seen with the use of cross-correlation. CONCLUSION: Autocorrelation and crosscorrelation have been shown to be an effective tool for several different applications in the movement sciences. Examples of the method’s utility include noise detection within a signal, determination of relative muscle activation onsets for postural control, objective quantification of muscle coactivation, and relating muscle activations with mechanical events.

J Orthop Sports Phys Ther 2009;39(4):287-295, Epub 17 December 2008. doi:10.2519/jospt.2009.2969

KEY WORDS: EMG, methodology, motor control