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Ear Hear. 2019 May 20. doi: 10.1097/AUD.0000000000000746. [Epub ahead of print]

The Revised Hearing Handicap Inventory and Screening Tool Based on Psychometric Reevaluation of the Hearing Handicap Inventories for the Elderly and Adults.

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Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA.
Department of Healthcare Leadership and Management, Medical University of South Carolina, Charleston, South Carolina, USA.



The present study evaluates the items of the Hearing Handicap Inventory for the Elderly and Hearing Handicap Inventory for Adults (HHIE/A) using Mokken scale analysis (MSA), a type of nonparametric item response theory, and develops updated tools with optimal psychometric properties.


In a longitudinal study of age-related hearing loss, 1447 adults completed the HHIE/A and audiometric testing at baseline. Discriminant validity of the emotional consequences and social/situational effects subscales of the HHIE/A was assessed, and nonparametric item response theory was used to explore dimensionality of the items of the HHIE/A and to refine the scales.


The HHIE/A items form strong unidimensional scales measuring self-perceived hearing handicap, but with a lack of discriminant validity of the two distinct subscales. Two revised scales, the 18-item Revised Hearing Handicap Inventory and the 10-item Revised Hearing Handicap Inventory-Screening, were developed from the common items of the original HHIE/A that met the assumptions of MSA. The items on both of the revised scales can be ordered in terms of increasing difficulty.


The results of the present study suggest that the newly developed Revised Hearing Handicap Inventory and Revised Hearing Handicap Inventory-Screening are strong unidimensional, clinically informative measures of self-perceived hearing handicap that can be used for adults of all ages. The real-data example also demonstrates that MSA is a valuable alternative to classical psychometric analysis.

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