Audiometric profiles and patterns of benefit: a data-driven analysis of subjective hearing difficulties and handicaps

Hearing rehabilitation attempts to compensate for auditory dysfunction, reduce hearing difficulties and minimise participation restrictions that can lead to social isolation. However, there is no systematic approach to assess the quality of the intervention at an individual level that might help to...

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Bibliographic Details
Published inInternational journal of audiology Vol. 61; no. 4; pp. 301 - 310
Main Authors Sanchez-Lopez, Raul, Dau, Torsten, Whitmer, William M.
Format Journal Article
LanguageEnglish
Published England Taylor & Francis 01.04.2022
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Summary:Hearing rehabilitation attempts to compensate for auditory dysfunction, reduce hearing difficulties and minimise participation restrictions that can lead to social isolation. However, there is no systematic approach to assess the quality of the intervention at an individual level that might help to evaluate the need of further hearing rehabilitation in the hearing care clinic. A data-driven analysis on subjective data reflecting hearing disabilities and handicap was chosen to explore "benefit patterns" as a result of rehabilitation in different audiometric groups. The method was based on (1) dimensionality reduction; (2) stratification; (3) archetypal analysis; (4) clustering; (5) item importance estimation. 572 hearing-aid users completed questionnaires of hearing difficulties (speech, spatial and qualities hearing scale; SSQ) and hearing handicap (HHQ). The data-driven approach revealed four benefit profiles that were different for each audiometric group. The groups with low degree of high-frequency hearing loss (HL HF ) showed a priority for rehabilitating hearing handicaps, whereas the groups with HL HF > 50 dB HL showed a priority for improvements in speech understanding. The patterns of benefit and the stratification approach might guide the clinical intervention strategy and improve the efficacy and quality of service in the hearing care clinic.
ISSN:1499-2027
1708-8186
DOI:10.1080/14992027.2021.1905890