The application of SHERPA (Systematic Human Error Reduction and Prediction Approach) in the development of compensatory cognitive rehabilitation strategies for stroke patients with left and right brain damage

Charmayne Hughes, Christopher Baber, Marta Bienkowicz, Andrew Worthington, Alexa Hazell, Joachim Hermsdorfer

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Approximately 33% of stroke patients have difficulty performing activities of daily living, often committing errors during the planning and execution of such activities. The objective of this study was to evaluate the ability of the human error identification (HEI) technique SHERPA (Systematic Human Error Reduction and Prediction Approach) to predict errors during the performance of daily activities in stroke patients with left and right hemisphere lesions. Using SHERPA we successfully predicted 36 of the 38 observed errors, with analysis indicating that the proportion of predicted and observed errors was similar for all sub-= tasks and severity levels. HEI results were used to develop compensatory cognitive strategies that clinicians could employ to reduce or prevent errors from occurring. This study provides evidence for the reliability and validity of SHERPA in the design of cognitive rehabilitation strategies in stroke populations.
Original languageEnglish
Article numberdx.doi.org/10/1080/00140139.2014.957735
Pages (from-to)75-95
Number of pages20
JournalErgonomics
Volume58
Issue number1
Early online date15 Sep 2015
DOIs
Publication statusPublished - 2015

Keywords

  • task analysis
  • human error identification
  • stroke;
  • cognitive therapy

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