SHOULDER LEFT/RIGHT JUDGEMENT TASK: DEVELOPMENT AND ESTABLISHMENT OF A POPULATION DATASET.  — YRD
  1. Schedule
  2. AGM and Afternoon Tea/Poster Viewing
  3. SHOULDER LEFT/RIGHT JUDGEMENT TASK: DEVELOPMENT AND ESTABLISHMENT OF A POPULATION DATASET. 

SHOULDER LEFT/RIGHT JUDGEMENT TASK: DEVELOPMENT AND ESTABLISHMENT OF A POPULATION DATASET.  (1870)

John Breckenridge 1 2 , James McAuley 3 , Lorimer Moseley 4 , David Butler 5 , Halton Stewart 5 , Karen Ginn 1
  1. Discipline of Biomedical Science, The University of Sydney, Sydney, NSW, Australia
  2. Sydney West Handtherapy, Sydney, NSW, Australia
  3. Neuroscience Research Australia, Sydney, NSW, Australia
  4. Sansom Institute for Health Research, University of South Australia, Adelaide, SA, Australia
  5. Neuro Orthopaedic Institute, Adelaide, SA, Australia

Background - The left/right judgement task (LRJT) is an implicit motor imagery task used to investigate and treat painful conditions such as complex regional pain syndrome. Shoulder problems have not been investigated using the LRJT. Chronic shoulder pain is common and can be difficult to manage. New treatments are required. A critical first step is to develop a shoulder specific LRJT.

Aims -  Develop and validate an online version of the LRJT specifically for the shoulder. Primary outcomes were mean response time (RT) and accuracy.  

Method - 1413 adult participants were recruited worldwide through social media, health professional networks and handtherapy clinics.
 A series of photographic images were chosen to represent the shoulder in a variety of standardised postures. These were delivered via a software program Recognise™. Participants viewed the randomly displayed shoulder images and identified whether they were left or right.

Results – There was an effect of shoulder posture. RTs were quickest for shoulder neutral and slowest for hand behind back (F=252.44, p< 0.001). The mean RT (SD) for the shoulder LRJT was 1738ms (741). Mean accuracy (SD) was 93.8% (9.2). RTs were slowest for images maximally rotated (F=623.06, p< 0.001).

Conclusion – The shoulder LRJT obeys the principles that have been established for the hand version of this task. Response times increase with the complexity of the shoulder posture. Participants use a motor imagery strategy to complete the shoulder LRJT. This dataset provides a foundation for further research with shoulder pain populations.