• Emma Sprague, Richard J Siegert, Oleg Medvedev, and Margaret H Roberts.
• Hospice West Auckland, Auckland, New Zealand.
• J Pain Symptom Manage. 2018 May 1; 55 (5): 1356-1363.

ContextThe Edmonton Symptom Assessment System (ESAS) is a widely used multisymptom assessment tool in cancer and palliative care settings, but its psychometric properties have not been widely tested using modern psychometric methods such as Rasch analysis.ObjectivesTo apply Rasch analysis to the ESAS in a community palliative care setting and determine its suitability for assessing symptom burden in this group.MethodsESAS data collected from 229 patients enrolled in a community hospice service were evaluated using a partial credit Rasch model with RUMM2030 software (RUMM Laboratory Pty, Ltd., Duncraig, WA). Where disordered thresholds were discovered, item rescoring was undertaken. Rasch model fit and differential item functioning were evaluated after each iterative phase.ResultsUniform rescoring was necessary for all 12 items to display ordered thresholds. The best model fit was achieved after item rescoring and combining three pairs of locally dependent items into three superitems (χ2 = 29.56 [27]; P = 0.33) that permitted ordinal-to-interval conversion.ConclusionThe ESAS satisfied unidimensional Rasch model expectations in a 12-item format after minor modifications. This included uniform rescoring of the disordered response categories and creating superitems to improve model fit and clinical utility. The accuracy of the ESAS scores can be improved by using ordinal-to-interval conversion tables published in the article.Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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