Muskuloskeletal Pain – Assessment, Prediction and Treatment: A Pragmatic Approach (EPUB)

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By David M. Walton, James M. Elliott, Guy Simoneau, Wellington K. Hsu Musculoskeletal Pain – Assessment, Prediction and Treatment presents a common sense approach to interpreting and applying existing clinical knowledge and new research to help clinicians make sense of the complex phenomena of acute and chronic post-traumatic musculoskeletal pain. Built upon the Assess, Predict, Treat framework, the authors offer a method to help clinicians better understand their patients’ pain. They present evidence-based decision tools to predict the natural and clinical course of common conditions, such as neck and low back pain, and they then synthesize that information into a…

SKU: MED-AMB113433
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By David M. Walton, James M. Elliott, Guy Simoneau, Wellington K. Hsu

Musculoskeletal Pain – Assessment, Prediction and Treatment presents a common sense approach to interpreting and applying existing clinical knowledge and new research to help clinicians make sense of the complex phenomena of acute and chronic post-traumatic musculoskeletal pain. Built upon the Assess, Predict, Treat framework, the authors offer a method to help clinicians better understand their patients’ pain. They present evidence-based decision tools to predict the natural and clinical course of common conditions, such as neck and low back pain, and they then synthesize that information into a logical, integrated treatment approach, which respects the individuality of the patient, the experiences of the clinician, and the value of evidence-informed practice.David Walton and James Elliott are leaders in the field of post-traumatic pain and recovery. Their work provides a valuable framework to facilitate novice clinicians in their transition towards experts and helps mid- and late-stage clinicians better interpret, synthesize, and discuss complex information on pain with the goal of optimised outcomes for patients.

Product Details

  • Publisher ‏ : ‎ Handspring Publishing; 1st edition (March 25, 2020)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 193 pages
  • ISBN-10 ‏ : ‎ 191208550X
  • ISBN-13 ‏ : ‎ 978-1912085507

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