Julia Hush

Professor

  • 1459 Citations
  • 23 h-Index
1988 …2018
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Personal profile

Biography

Professional Overview

Hush is a Professor of Physiotherapy in Macquarie University’s Department of Health Professions. She is a Foundation Academic and Department Director of Research. Her main areas of clinical expertise is pain management. Her current research program includes clinical pain neuroscience, paediatric pain, personalised pain treatment for low back pain, neuropathic pain and exercise-induced analgesia.

Hush’s current research in health science is founded on a decade of basic science research, during which time she made discoveries in the field of cell science, specifically about the dynamics and electrophysiological regulation of the microtubule cytoskeleton. This work continues to have impact in the field.

Hush has attained over $1.7M in research funding, including grants from the ARC, NHMRC and IASP. She has published >70 papers in peer-reviewed journals, including Journal of Cell Science, Pain, Cerebral Cortex, Clinical Journal of Pain, Arthritis & Rheumatism, Archives of Physical Medicine & Rehabilitation, European Spine Journal, and Journal of Physiotherapy. She has an H-index of 28 and over 2075 citations (Google Scholar May 2018). She is a Section Editor for the Journal of Physiotherapy and is an invited reviewer for over 20 international journals, including New England Journal of Medicine and Annals of Internal Medicine. She currently supervises 4 PhD students.

Hush has been engaged in collaborative pain neuroscience research with Professor Sean Mackey the Stanford Systems Neuroscience and Pain Lab (SNAPL), at Stanford University since 2008, supported by an International Association of the Study of Pain (IASP) Collaborative Research Grant.

Since her appointment at Macquarie University, Hush has had a leadership role in the development and delivery of the Doctor of Physiotherapy entry-level program, first delivered in 2012. Her areas of teaching expertise include clinical pain science, evidence-based healthcare and musculoskeletal physiotherapy. She has led the integration of the IASP Pain Curriculum into the Doctor of Physiotherapy program. She is currently engaged in teaching in the new Macquarie MD program, in Musculoskeletal medicine, as well as leading interprofessional education between the Doctor of Physiotherapy and Macquarie MD programs in Evidence-Based Health Care.

In 2018, Hush was awarded Fellowship of the Royal Society of NSW.

Since January 2016 she has worked part-time (0.6FTE).

External positions

Visiting Associate Professor, Stanford University School of Medicine

Jul 2013Dec 2013

Associate Editor, BioMed Central (BMC) Musculoskeletal Disorders

20132014

Scientific Program Committee Member, Australian Pain Society

20122017

Editorial Board Member, International Society of Physiotherapy Journal Editors

2009 → …

Editorial Board Member, Journal of Physiotherapy

2009 → …

Visiting Associate Professor, Stanford University School of Medicine

Aug 2008Dec 2008

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Projects 2012 2016

Research Output 1988 2018

A child’s concept of pain: an international survey of pediatric pain experts

Pate, J. W., Hush, J. M., Hancock, M. J., Moseley, G. L., Butler, D. S., Simons, L. E. & Pacey, V. 2018 In : Children. 5, 1, p. 1-11 11 p., 12

Research output: Contribution to journalArticle

Open Access
File
Pediatrics
Pain
Surveys and Questionnaires
Biological Phenomena
Expert Testimony

Effect of intensive patient education vs placebo patient education on outcomes in patients with acute low back pain: a randomized clinical trial

Traeger, A. C., Lee, H., Hubscher, M., Skinner, I. W., Moseley, G. L., Nicholas, M. K., Henschke, N., Refshauge, K. M., Blyth, F. M., Main, C. J., Hush, J. M., Lo, S. & McAuley, J. H. 5 Nov 2018 In : JAMA Neurology.

Research output: Contribution to journalArticle

Patient Education
Low Back Pain
Randomized Controlled Trials
Placebos
Pain
Open Access
File
Open Access
File
Low Back Pain
Pain
Pain Threshold
Psychology
Pressure
Chronic Pain
Psychology
Pain
Cognitive Therapy
Cluster Analysis