Published in:
Open Access 01-12-2020 | Research
Item analysis of the Eating Assessment Tool (EAT-10) by the Rasch model: a secondary analysis of cross-sectional survey data obtained among community-dwelling elders
Published in: Health and Quality of Life Outcomes | Issue 1/2020
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Background
The Eating Assessment Tool (EAT-10) is increasingly used to screen for self-perceived oropharyngeal dysphagia (OD) in community-dwelling elders. A summated EAT-10 total score ranges from 0 to 40, with a score ≥ 3 indicative of OD. When using cut-points of a summated score, important requirements for the measurements are specific objectivity, validity, and reliability. Analysis by the Rasch model allows investigation of whether scales like EAT-10 satisfy these requirements. Currently, a few studies have found that EAT-10 responses from clinical populations with OD do not adequately fit the Rasch model.
Purpose
The aim of this study was to determine whether measurements by EAT-10 fit the Rasch model when applied in screening self-perceived OD in non-clinical populations.
Methods
Secondary analysis was conducted on data from a cross-sectional survey of community-dwelling elders living in a municipal district of Tokyo, Japan, in which 1875 respondents completed the Japanese version of EAT-10 (J-EAT-10). Data were cleaned and recoded for the purpose of the analysis in this study, which resulted in inclusion of J-EAT-10 responses from 1144 respondents. Data were analyzed using RUMM2030 and included overall model fit, reliability, unidimensionality, threshold ordering, individual item and person fits, differential item functioning, local item dependency, and targeting.
Results
The analysis identified that the response categories from zero to four were not used as intended and did not display monotonicity, which necessitated reducing the five categories to three. Considerable floor effect was demonstrated and there was an inappropriate match between items’ and respondents’ estimates. The person separation reliability (PSI = 0.65) was inadequate, indicating that it is not possible to differentiate between different levels of OD. Several items displayed misfit with the Rasch model, and there were local item dependency and several redundant items.
Conclusions
J-EAT-10 performed less than optimally and exhibited substantial floor effect, low reliability, a rating scale not working as intended, and several redundant items. Different improvement strategies failed to resolve the identified problems. Use of J-EAT-10 in population-based surveys cannot therefore be recommended. For such purpose, alternative screening tools of self-perceived OD should be chosen or a new one should be developed and validated.