Application of Rasch Analysis to the Evaluation of the Measurement Properties of the Hearing Handicap Inventory for the Elderly

Ear Hear. 2020 Sep/Oct;41(5):1125-1134. doi: 10.1097/AUD.0000000000000832.

Abstract

Objectives: The aim of this research was to evaluate the measurement properties of the Hearing Handicap Inventory for the Elderly (HHIE). The HHIE is one of the most widely used patient-reported outcome measures in audiology. It was originally developed in the United States in the 1980s as a measure of the social and emotional impact of hearing loss in older adults. It contains 25 items that are accompanied by a 3-point response scale. To date, the measurement properties of the HHIE have primarily been assessed via traditional psychometric analysis techniques (e.g., Cronbach's alpha and Principal Components Analysis). However, traditional techniques are now known to have several limitations in comparison to more modern approaches. Therefore, this research used a modern psychometric analysis technique, namely Rasch analysis, to evaluate the HHIE.

Design: Rasch analysis was performed on HHIE data collected from 380 adults with hearing loss. The participants were principally recruited from the participant database of the National Institute for Health Research Nottingham Biomedical Research Centre in the United Kingdom. Additional participants were recruited from two UK audiology clinics and the online forum of a UK hearing loss charity. Rasch analysis was used to assess the measurement properties of the HHIE (i.e., fit to the Rasch model, unidimensionality, targeting, and person separation reliability) and its individual items (i.e., response dependency, fit, Differential Item Functioning, and threshold ordering).

Results: The HHIE was found to have several strong measurement properties. Specifically, it was well-targeted and had high person separation reliability. However, it displayed poor fit to the Rasch model and was not unidimensional. The majority of the items were free of response dependency (i.e., redundancy) and were suited to the 3-point response scale. However, two items were found to be better suited to a dichotomous response scale. Furthermore, nine items were identified as being candidates for removal from the questionnaire, as they exhibited poor fit and/or Differential Item Functioning (i.e., item bias) associated with gender. The measurement properties of the HHIE could be improved by removing these items and adjusting the scores of the two items that require a dichotomous response scale. These amendments resulted in a 16-item version of the HHIE that had good fit to the Rasch model and that was unidimensional.

Conclusions: It is vital to ensure that high-quality outcome measures are used in audiology research and practice. This study evaluated one of the foremost outcome measures in this field: the HHIE. The results demonstrated that the HHIE had several strong measurement properties. Amending the HHIE, such as by removing items exhibiting poor fit, could further enhance its quality. A unique aspect of this study was the application of Rasch analysis to the evaluation of the HHIE. It is recommended that future studies use modern techniques to develop and identify high-quality, hearing-specific outcome measures.

MeSH terms

  • Aged
  • Hearing*
  • Humans
  • Psychometrics
  • Quality of Life*
  • Reproducibility of Results
  • Surveys and Questionnaires
  • United Kingdom