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The Efficacy of Waddell Signs to Predict Delayed Return to Work in Patients with Work-restricting Low Back Pain

1 May 2007


1. Clinical Bottom Line: Waddell’s signs and symptoms are not effective for predicting delay or non-return to work in patients with work restricting low back pain.

2. Clinical Scenario: In the outpatient orthopedic setting, clinicians play a large role in the treatment of patients with work-restricting low back pain. A majority of these patients experience chronic low back pain, enabling them from return to work in a timely fashion and increasing health care costs and compensation benefits dispersed. As a clinician, you hope to utilize specific tools that will validly predict the outcome of physical therapy treatment; and more specifically in this case, return to work. While working with a veteran clinician, we observed the use of Waddell signs as a predictive tool for patients with chronic work-restricting low back pain. A majority of the patients were taking part in a work hardening program where a clinical psychologist was available for consultation and intervention. Many others, not a part of the work hardening program, were receiving compensation benefits. There was a wide range of patients seen by this clinician, but every initial evaluation included a screening for Waddell signs. However, the use of these signs as a predictive tool for non-return to work is not a topic discussed readily amongst health professionals, and within the physical therapy school curriculum. Thus, to determine the validity and efficacy of these signs we established the following clinical question: Are Waddell Signs an effective predictive test for delayed or non-return to work in patients with low back pain?

3. Our Clinically Answerable Question: Population: Patients with low back pain, unable to perform full time work duties. Independent Variable: Physical examination for the presence of Waddell signs. Comparison: Return to full time work. Outcome Measure(s): Efficacy of Waddell signs measured by sensitivity, specificity, predictive values, and likelihood ratios.


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