We found that neither the side of the ear nor gender influenced the APHAB
u score. This finding is in concordance with those of previously published reports. The mean age of our group of participants was younger than studies that included subjects with are subsequently fitted with hearing aids [
7,
9,
10]. According to previous results, the AV subscale is different for all others. Measuring the aversiveness of sounds due to very similar APHAB
u scores in both investigated groups (normal hearing and with hearing loss), as demonstrated in Table
2. Using single subscales of APHAB
u (EC, BN, and RV) leads to nearly similar cutoff values for EC
u and RV
u, and, by comparison, the cutoff score for BN
u was even higher (Table
4). This may be explained by more widespread individual compensation abilities for hearing loss, as shown previously [
9,
10]. In addition, the cutoff vaulue for the average model (Eq.
1) due to a value (0.15) which is closer to the values of EC
u (0.10) and RV
u (0.12) than the BN
u value (0.23) by the single use of the subscales. As has been reported, BN subscale scores are not associated with individual hearing loss [
7]. Maybe, the lower APHAB
u values of the normal hearing group in EC and RV (Table
2) could support this thesis. In addition, the sensitivity using single subscales is resulting in different values around 0.70 and 0.84, whereas the mean subscale (Eq.
1) is 0.76. Although both models are due to values within the confidence intervals, the average model (Eq.
1) may be superior to use of the individual subscales. At least, it is simpler to use one value in sensitivity and specificity than three. This level of sensitivity and specificity is as high as that of other inventories, such as the hearing handicap inventory for the elderly screening version (HHIE-S, [
18]) and the Mini-Audio-Test (MAT, [
19]). Subjects in the group with false-negative results may ignore their hearing problems, or they may be able to compensate for their hearing impairment. An alternative model is the logistic regression model (Eq.
2b), which uses the constants from Table
5. This model has an even higher level of sensitivity, but its specificity is slightly lower than that of the average model (Eq.
1).
It might be surprising that a hearing loss of 25 dB has an influence on APHAB
u scores. In fact, including 8.0 kHz might be very strict and not used in MAT [
19], and increases at least the number of healthy or sick ears. But our findings confirm previous results [
7,
10]. In addition, such an influence of 8.0 kHz has been detected for the HHIE-S as well [
20]. In contrast to the APHAB, the HHIE-S and the MAT are developed for screening use only. The APHAB is too large to play an important role in screening. Nevertheless, sensitivity and specificity are required characteristics for inventories in general [
12].
At present, some rather difficult methods in conjunction with the APHAB to measure the quality of hearing aid fitting in patients with statutory insurance are used in Germany [
3,
4]. They calculate relations of the differences of subscales to their means which can due to some problems in the result by arithmetic reasons. Of course, these methods are based on the difference of two APHAB forms, before and after hearing aid fitting. But going forward, it may be of benefit to patient and clinicians to instead use modified Eqs. (
1) or (
2a) for quality measurement of hearing aid fitting as well. However, further research is required to validate our results with these models. These models may be of particular benefit in cases in which the APHAB
u is being used as a screening inventory or as a primary audiological diagnostic method. Use of the logistic regression model to determine the diagnostic value of the APHAB
u may be justified by the weighted influence of the RV subscale. Recent investigations have found that the likelihood of individual compensatory effects is highest for BN and lowest for RV and that the influence of the EC subscale is limited to cases with increased hearing loss [
7,
10]. In summary, our determination of the sensitivity and specificity of the APHAB
u adds to the knowledge of this widely used inventory in Germany. We suggest that future studies investigate the values of these parameters separately for each frequency. Together with the recently published percentile distribution curves and box plots of the unaided and aided APHAB and the resulting benefit [
21] and together with the knowledge of mutual dependencies of APHAB
u scores, pure-tone thresholds, and speech-audiometric results, it is well possible to interpret an individual hearing loss.