APHAB scores for individual assessment of the benefit of hearing aid fitting

• Published in: HNO Vol. 65; no. 11; pp. 901 - 909
• Main Authors: Löhler, J, Wollenberg, B, Schönweiler, R
• Format: Journal Article
• Language: German
• Published: Germany 01.11.2017
• Subjects: Auditory Perception; Hearing Aids; Hearing Loss; Humans; Prosthesis Fitting; Surveys and Questionnaires; Benefit assessment; Persons with hearing impairments; Hearing disorders; Questionnaires; Hearing loss
• ISSN: 1433-0458
• DOI: 10.1007/s00106-017-0350-z

The Abbreviated Profile of Hearing Aid Benefit (APHAB) questionnaire measures subjective hearing impairment on four different subscales pertaining to different listening situations. Using a very large patient cohort, this study aims to show how answers are distributed within the four subscales before and after hearing aid fitting, and what benefit the patients experience. The results are discussed on the basis of the available literature. Between April 2013 and March 2016, 35,000 APHAB questionnaires from nine German statutory health insurance providers were evaluated. The average values before and after hearing aid fitting, as well as the benefit, were determined for all four APHAB subscales and analyzed graphically. The results of the subjective evaluation of hearing impairment before and after hearing aid fitting and the resultant benefit were plotted by percentile distribution graphs and boxplots. The data were analyzed statistically. There was no overlap of the interquartile ranges before and after hearing aid fitting in any of the APHAB subscales. In three scales (EC, BN and RV), the median improvement after hearing aid fitting was nearly 30 percentage points. In the AV subscale, this value was slightly negative. The percentile distribution graphs used in this study allow individual evaluation of subjective hearing impairment before and after hearing aid fitting, as well as of the resultant benefit, on the background of a huge database. Additionally, it is demonstrated why presentation as boxplots and the average benefit values calculated from these is problematic.