Associations between the probabilities of frequency-specific hearing loss and unaided APHAB scores

[Correlation between the APHAB questionnaire and the Freiburg monosyllabic test without + with noise]

BACKGROUND

Questionnaires, e. g. the APHAB, and speech-audiometry are the most used elements in measuring the success of hearing aid fitting (HAF). This study investigates the correlations between the results of the Freiburg monosyllabic word test without and with noise (FBE, FBE-S) and the results of the APHAB before and after HAF.

METHODS

Data of the FBE, the FBE-S, and the APHAB, generated within HAF of 156 subjects were analyzed. After exclusion of a normal distribution of the data, Spearman's correlation and Cohen's effect size were determined.

RESULTS

73 (46.8 %) of the 156 subjects were females, and 83 (53.2 %) males. No significant correlation could be found between the EC-, the RV-, and the cumulative ECBNRV-subscale and the benefit of HAF in the FBE and FBE-S (EC: ease of communication, BN: background noise, RV: reverberation). Most of the remaining coefficients of correlation had a weak positive effect size. A middle positive effect size could only be demonstrated for 6 combinations, for the EC-subscale mostly.

CONCLUSION

The not strong effect sizes could assume that the results in speech-audiometry and the APHAB are not independent and complementing each other as parameters of hearing loss and benefit in HAF. The effect size could be explained by individually different possibilities for the compensation of hearing loss.

Clinical Application and Psychometric Properties of a Swedish Translation of the Abbreviated Profile of Hearing Aid Benefit

BACKGROUND

The impact of hearing loss on the individual and his/her everyday life can be assessed using questionnaires with the purpose to improve rehabilitation quality. The Abbreviated Profile of Hearing Aid Benefit (APHAB) can be used to evaluate disability in everyday life associated with hearing loss. Previous studies have examined APHAB outcomes in sensorineural hearing loss and we do not know whether the type of hearing loss influence questionnaire outcomes.

PURPOSE

The purpose was to evaluate the psychometric properties of a Swedish translation of the APHAB and the influence of demographic variables on the outcome in a clinical sample.

RESEARCH DESIGN

A descriptive, cross-sectional study in a clinical sample.

STUDY SAMPLE

Forty-eight participants with no hearing aid experience seeking audiological rehabilitation for the first time. These participants represented different degrees of hearing loss and three types of hearing loss: monaural mixed, binaural mixed, and binaural sensorineural hearing loss.

DATA COLLECTION AND ANALYSIS

Pure-tone audiometry was conducted and the participants completed the unaided APHAB during their first appointment at the clinic. Psychometric properties of the questionnaire were examined and the influence of age, gender, type of hearing loss, and degree of hearing loss on APHAB scores were studied.

RESULTS

The psychometric properties indicate high test-retest reliability but there seems to be some potential issues with the properties of the reverberation (RV) subscale. The items from the RV subscale failed to load as a separate component and the internal consistency of the subscale improved by removing four items (items 1, 9, 11, and 16). With few exceptions, APHAB scores were not influenced by age, gender, or type of hearing loss. APHAB scores were generally influenced by degree of hearing loss in both the best and the worst ear.

CONCLUSION

This Swedish version of the APHAB can be additionally improved by addressing the inconsistencies found in the RV subscale by rephrasing or removing some items. The degree of hearing loss has some influence on questionnaire outcomes but not age, gender, and type of hearing loss.

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

OBJECTIVE

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.

PATIENTS AND METHODS

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.

RESULTS

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.

DISCUSSION

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.

Sensitivity and specificity of the abbreviated profile of hearing aid benefit (APHAB)

Subjective hearing loss in hearing-impaired patients can be assessed by inventory questionnaires. The abbreviated profile of hearing aid benefit (APHAB) measures subjective hearing loss in four typical hearing situations (subscales). It is used to fit hearing aids in patients with statutory insurance in Germany. In addition, the unaided APHAB (APHAB_u) can be used as a primary diagnostic instrument in audiology. There are no published data regarding the sensitivity and specificity of the unaided APHAB_u. Therefore, we investigated these parameters for detecting hearing loss of at least 25 dB at any frequency between 0.5 and 8.0 kHz. We used the APHAB_u to determine hearing loss in 245 subjects aged 50 years and older without any reported disease of the ears. Due to incomplete answering of the APHAB form, 55 subjects have been excluded. We also measured the pure-tone thresholds by air conduction for all octave frequencies between 0.5 and 8 kHz. Receiver operating characteristic (ROC) curves and the Youden Index were used to determine the diagnostic value of the APHAB_u, particularly sensitivity and specificity, in three different ways: (1) separately for ease of communication (EC_u), background noise (BN_u), and hearing with reverberation (RV_u) subscales; (2) with the mean value of EC_u, BN_u, and RV_u; and (3) with a logistic regression model. The area under the ROC curve was lower for BN only (0.83) and nearly equal for all other methods (0.87–0.89). Depending on how we performed the analyses, the sensitivity of the APHAB_u was 0.70–0.84 (single subscales), 0.76 (mean value of EC_u, BN_u, and RV_u), or 0.85 (logistic regression model). The specificity was 0.79–0.95. The use of single APHAB_u subscales for determining the sensitivity and specificity of the APHAB_u due to confusing results. In comparison, the use of the mean value of EC_u, BN_u, and RV_u and the use of the logistic regression model due to equal values in the ROC curves but a higher sensitivity in the logistic regression model. Therefore, we would recommend the last method for determining the sensitivity and specificity of the APHAB_u.