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Rasch analysis of the Back Pain Attitudes Questionnaire (Back-PAQ).

Christian U KrägelohOleg N MedvedevSarah Gerard DeanJames StanleyAnthony DowellBen Darlow
Published in: Disability and rehabilitation (2020)
The ordinal-to-interval conversion algorithms presented here further enhance the precision of the scale and permit analysis of Back-PAQ-20 scores using parametric statistics. The present study provided evidence for valid and reliable assessment of the back pain recovery beliefs of both users as well as providers of health services.IMPLICATIONS FOR REHABILITATIONPsychosocial factors have been recognised as significant predictors of the recovery trajectory from chronic back pain.The 34-item Back Pain Attitudes Questionnaire (Back-PAQ) was developed based on themes obtained from patient interviews, but previous psychometric analyses with a general population sample revealed uncertainty around the factor structure of the instrument.The 20-item version of the Back Pain Attitudes Questionnaire (Back-PAQ) is shown here to have strong psychometric properties for administration with users and providers of health services.
Keyphrases
  • psychometric properties
  • mental health
  • machine learning
  • case report
  • deep learning
  • single cell
  • patient reported outcomes
  • drug induced
  • clinical evaluation