Exploring Factors That Contribute to the Success of Rehabilitation With Hearing Aids.

OBJECTIVES: Hearing aids are an essential and important part of hearing rehabilitation. The combination of technical data on hearing aids and individual rehabilitation needs can give insight into the factors that contribute to the success of rehabilitation. This study sets out to investigate if different subgroups of (comparable) hearing aids lead to differences in the success of rehabilitation, and whether these differences vary between different domains of auditory functioning. DESIGN: This study explored the advantages of including patient-reported outcome measures (PROMs) in the process of purchasing new hearing aids in a large sample of successful hearing aid users. Subject data were obtained from 64 (commercial) hearing aid dispensers and 10 (noncommercial) audiological centers in the Netherlands. The PROM was a 32-item questionnaire and was used to determine the success of rehabilitation using hearing aids by measuring auditory disability over time. The items were mapped on six domains of auditory functioning: detection, discrimination, localization, speech in quiet, speech in noise, and noise tolerance, encompassing a variety of daily-life listening situations. Hearing aids were grouped by means of cluster analysis, resulting in nine subgroups. In total, 1149 subjects were included in this study. A general linear model was used to model the final PROM results. Model results were analyzed via a multifactor Analysis of Variance. Post hoc analyses provided detailed information on model variables. RESULTS: Results showed a strong statistically significant effect of hearing aids on self-perceived auditory functioning in general. Clinically relevant differences were found for auditory domains including detection, speech in quiet, speech in noise, and localization. There was only a small, but significant, effect of the different subgroups of hearing aids on the final PROM results, where no differences were found between the auditory domains. Minor differences were found between results obtained in commercial and noncommercial settings, or between novice and experienced users. Severity of Hearing loss, age, gender, and hearing aid style (i.e., behind-the-ear versus receiver-in-canal type) did not have a clinically relevant effect on the final PROM results. CONCLUSIONS: The use of hearing aids has a large positive effect on self-perceived auditory functioning. There was however no salient effect of the different subgroups of hearing aids on the final PROM results, indicating that technical properties of hearing aids only play a limited role in this respect. This study challenges the belief that premium devices outperform basic ones, highlighting the need for personalized rehabilitation strategies and the importance of evaluating factors contributing to successful rehabilitation for clinical practice.

Classification of Hearing Aids Into Feature Profiles Using Hierarchical Latent Class Analysis Applied to a Large Dataset of Hearing Aids.

OBJECTIVES: We developed a framework for objectively comparing hearing aids, independent of brand, type, or product family. This was done using a large dataset of commercially available hearing aids. To achieve this, we investigated which hearing aid features are suitable for comparison, and are also relevant for the rehabilitation of hearing impairment. To compare hearing aids objectively, we distinguished populations of hearing aids based on a set of key hearing aid features. Finally, we describe these hearing aid subpopulations so that these could potentially be used as a supporting tool for the selection of an appropriate hearing aid. DESIGN: In this study, we used technical (meta-)data from 3911 hearing aids (available on the Dutch market in March 2018). The dataset contained about 50 of the most important characteristics of a hearing aid. After cleaning and handling the data via a well-defined knowledge discovery in database procedure, a total 3083 hearing aids were included. Subsequently, a set of well-defined key hearing aid features were used as input for further analysis. The data were split into an in-the-ear style hearing aid subset and a behind-the-ear style subset, for separate analyses. The knowledge discovery in databases procedure was also used as an objective guiding tool for applying an exploratory cluster analysis to expose subpopulations of hearing aids within the dataset. The latter was done using Latent Class Tree Analysis, which is an extension to the better-known Latent Class Analysis clustering method: with the important addition of a hierarchical structure. RESULTS: A total of 10 hearing aid features were identified as relevant for audiological rehabilitation: compression, sound processing, noise reduction (NR), expansion, wind NR, impulse (noise) reduction, active feedback management, directionality, NR environments, and ear-to-ear communication. These features had the greatest impact on results yielded by the Latent Class Tree cluster analysis. At the first level in the hierarchical cluster model, the two subpopulations of hearing aids could be divided into 3 main branches, mainly distinguishable by the overall availability or technology level of hearing aid features. Higher-level results of the cluster analysis yielded a set of mutually exclusive hearing aid populations, called modalities. In total, nine behind-the-ear and seven in-the-ear modalities were found. These modalities were characterized by particular profiles of (complex) interplay between the selected key features. A technical comparison of features (e.g., implementation) is beyond the scope of this research. CONCLUSIONS: Combining a large dataset of hearing aids with a probabilistic hierarchical clustering method enables analysis of hearing aid characteristics which extends beyond product families and manufacturers. Furthermore, this study found that the resulting hearing aid modalities can be thought of as a generic alternative to the manufacturer-dependent proprietary "concepts," and could potentially aid the selection of an appropriate hearing aid for technical rehabilitation. This study is in line with a growing need for justification of hearing aid selection and the increasing demand for evidence-based practice.

Hearing Disabilities and the Effectiveness of Rehabilitation in Different Age Groups.

OBJECTIVE: To assess differences in hearing disabilities between different age groups and the effectiveness of rehabilitation with hearing aids. STUDY DESIGN: Retrospective chart review. SETTING: First line hearing aid dispensers. PATIENTS: First-time hearing aid users divided in a younger group aged 18 to 65 years (119 subjects) and an elderly group aged 70 years and older (213 subjects). INTERVENTION(S): Rehabilitative. MAIN OUTCOME MEASURE(S): Weighted pure tone averages (PTA) were calculated using the binaural impairment model. The patient-reported outcome measures (PROMs) Amsterdam Questionnaire for Auditory Disabilities (AVAB), and client oriented scale of improvement (COSI) were collected pre- and post-fitting. To analyze whether age group, weighted PTA, and type of auditory dimension influences AVAB, linear regression and two-way ANalysis Of VAriance models were used. RESULTS: The weighted PTA of the young group was significantly lower than of the elderly group. In the regression model differences between age groups were found to be significant for pre-AVAB and for AVAB benefit. The two-way ANalysis Of VAriance showed that the effect of age on pre- and post-AVAB scores was not influenced by PTA or the type of auditory dimension. CONCLUSIONS: Younger first-time hearing aid users experience more auditory disabilities, despite better hearing levels than their elderly counterparts. Their disabilities are rehabilitated more effectively by hearing aids.

Classification of Hearing Aids Into Feature Profiles Using Hierarchical Latent Class Analysis Applied to a Large Dataset of Hearing Aids.

OBJECTIVES: We developed a framework for objectively comparing hearing aids, independent of brand, type, or product family. This was done using a large dataset of commercially available hearing aids. To achieve this, we investigated which hearing aid features are suitable for comparison, and are also relevant for the rehabilitation of hearing impairment. To compare hearing aids objectively, we distinguished populations of hearing aids based on a set of key hearing aid features. Finally, we describe these hearing aid subpopulations so that these could potentially be used as a supporting tool for the selection of an appropriate hearing aid. DESIGN: In this study, we used technical (meta-)data from 3911 hearing aids (available on the Dutch market in March 2018). The dataset contained about 50 of the most important characteristics of a hearing aid. After cleaning and handling the data via a well-defined knowledge discovery in database procedure, a total 3083 hearing aids were included. Subsequently, a set of well-defined key hearing aid features were used as input for further analysis. The data were split into an in-the-ear style hearing aid subset and a behind-the-ear style subset, for separate analyses. The knowledge discovery in databases procedure was also used as an objective guiding tool for applying an exploratory cluster analysis to expose subpopulations of hearing aids within the dataset. The latter was done using Latent Class Tree Analysis, which is an extension to the better-known Latent Class Analysis clustering method: with the important addition of a hierarchical structure. RESULTS: A total of 10 hearing aid features were identified as relevant for audiological rehabilitation: compression, sound processing, noise reduction (NR), expansion, wind NR, impulse (noise) reduction, active feedback management, directionality, NR environments, and ear-to-ear communication. These features had the greatest impact on results yielded by the Latent Class Tree cluster analysis. At the first level in the hierarchical cluster model, the two subpopulations of hearing aids could be divided into 3 main branches, mainly distinguishable by the overall availability or technology level of hearing aid features. Higher-level results of the cluster analysis yielded a set of mutually exclusive hearing aid populations, called modalities. In total, nine behind-the-ear and seven in-the-ear modalities were found. These modalities were characterized by particular profiles of (complex) interplay between the selected key features. A technical comparison of features (e.g., implementation) is beyond the scope of this research. CONCLUSIONS: Combining a large dataset of hearing aids with a probabilistic hierarchical clustering method enables analysis of hearing aid characteristics which extends beyond product families and manufacturers. Furthermore, this study found that the resulting hearing aid modalities can be thought of as a generic alternative to the manufacturer-dependent proprietary "concepts," and could potentially aid the selection of an appropriate hearing aid for technical rehabilitation. This study is in line with a growing need for justification of hearing aid selection and the increasing demand for evidence-based practice.

Evaluation of Auditory Functioning and Rehabilitation Using Patient-Reported Outcome Measures.

There is lack of a systematic approach concerning how to select an adequate hearing aid and how to evaluate its efficacy with respect to the personal needs of rehabilitation. The goal of this study was to examine the applicability and added value of two widely used self-reporting questionnaires in relation to the evaluation of hearing aid fitting. We analyzed responses, pre- and postfitting, from 1,319 subjects who completed the Client Oriented Scale of Improvement (COSI) and a slightly adapted version of the Amsterdam Inventory for Auditory Disability and Handicap (in Dutch: AVAB). Most COSI responses were at or near the maximum possible score. Results show a close relation between COSI's degree of change and final ability (Spearman's rho = 0.71). Both AVAB and COSI showed a significant effect of hearing aid experience, but-in contrast to AVAB-COSI did not show a significant effect of the degree of hearing loss. In addition, a Friedman test showed significant differences between six dimensions of auditory functioning for both AVAB and COSI, although post hoc analysis revealed that for COSI, the dimension speech in quiet explained most variation between dimensions. In conclusion, the effects of hearing loss were more salient in AVAB, while both AVAB and COSI showed differences regarding hearing aid experience. Combining the advantages of both methods results in a detailed evaluation of hearing aid rehabilitation. Our results therefore suggest that both methods should be used in a complementary manner, rather than separately.