title: Discriminating between individuals with and without musculoskeletal disorders of the upper extremity by means of items related to computer keyboard use.
abstract: BACKGROUND
  Identifying postures and behaviors during keyboard use that can discriminate between individuals with and without musculoskeletal disorders of the upper extremity (MSD-UE) is important for developing intervention strategies. This study explores the ability of models built from items of the Keyboard-Personal Computer Style instrument (K-PeCS) to discriminate between subjects who have MSD-UE and those who do not.
  
  
  METHODS
  Forty-two subjects, 21 with diagnosed MSD-UE (cases) and 21 without MSD-UE (controls), were videotaped while using their keyboards at their onsite computer workstations. These video clips were rated using the K-PeCS. The K-PeCS items were used to generate models to discriminate between cases and controls using Classification and Regression Tree (CART) methods.
  
  
  RESULTS
  Two CART models were generated; one that could accurately discriminate between cases and controls when the cases had any diagnosis of MSD-UE (69% accuracy) and one that could accurately discriminate between cases and controls when the cases had neck-related MSD-UE (93% accuracy). Both models had the same single item, "neck flexion angle greater than 20 degrees ". In both models, subjects who did not have a neck flexion angle of greater than 20 degrees were accurately identified as controls.
  
  
  CONCLUSIONS
  The K-PeCS item "neck flexion greater than 20 degrees " can discriminate between subjects with and without MSD-UE. Further research with a larger sample is needed to develop models that have greater accuracy.
authors.affiliation: Department of Occupational Therapy, University of Pittsburgh, 5012 Forbes Tower, Pittsburgh, PA 15260, USA. nab36@pitt.edu
authors.forename: Nancy A
authors.initials: NA
authors.lastname: Baker
authors.forename: Nancy B
authors.initials: NB
authors.lastname: Sussman
authors.forename: Mark S
authors.initials: MS
authors.lastname: Redfern
mesh_terms: D000328:Adult; D016287:Computer Peripherals; D003663:Decision Trees; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D009140:Musculoskeletal Diseases / Q000175:diagnosis* / Q000453:epidemiology; D009784:Occupational Diseases / Q000175:diagnosis* / Q000453:epidemiology; D011187:Posture; D013647:Task Performance and Analysis; D034941:Upper Extremity