PP1108 - Noise Control Algorithm Reduces Listening Effort for Adolescents Who Are Bilateral Hearing Aid Users

Rationale: Hearing aid noise cleaning technologies, such as digital noise reduction and directional microphones, aim to mitigate listening challenges with poor signal-to-noise ratios. However, access to these technologies is not routinely recommended for school-age hearing aid users due to uncertainty that children could reliably alter noise cleaning technology for optimal listening. This study aims to evaluate if adolescents prefer noise cleaning technology on (vs off) in noisy environments and if they can reliably manipulate this setting in a remote-control smartphone app. Another purpose is to investigate whether advanced noise cleaning improves speech recognition scores or listening effort (measured subjectively and behaviorally) in a noisy environment.  

Methods: In this double-blind study, 18 participants (aged 10-17) were fit with research hearing aids, completed several laboratory visits, and wore the hearing aids home during a field trial. In the laboratory, participants completed speech-in-noise tasks, including: a) A-B, paired comparison testing to determine their preferred noise cleaning setting (off, weak, strong), b) an evaluation of their ability to manipulate noise cleaning settings in an app, and c) dual-task testing to evaluate word recognition performance and listening effort with and without noise cleaning. During the field trial, participants were encouraged to adjust the noise cleaning setting using the app while in noisy situations. After the field trial, data from the app were collected in the laboratory to evaluate participants’ preferred noise cleaning setting. Word recognition scores, subjective ratings of listening effort, and secondary dual-task response times were analyzed using linear mixed-effects models with ‘setting’ as a within-participant factor and ‘participant’ as a random intercept.  

Results:   Most participants (76%) preferred the noise cleaning algorithm to be active during paired comparisons testing. Participants‘ preferences for the noise cleaning technology were generally consistent between the laboratory tasks and field trial. Specifically, the two participants who preferred ‘off’ to ‘on’ during paired-comparison testing also set the noise cleaning algorithm to be inactive using the smartphone app during the field trial. Conversely, p</span>articipants who demonstrated a consistent preference for active noise cleaning during paired-comparison testing also used the app to activate noise cleaning in the laboratory setting. Mixed-effects modelling revealed activating noise cleaning algorithm did not negatively affect word recognition performance in noise. Subjective ratings of listening effort were lower (better) with the algorithm set to ‘strong’ than when disabled or set to ‘weak.’ Benefit for listening effort is dependent upon the setting evaluated and subjective vs behavioral listening effort.  Behavioral listening effort was reduced with participants’ customized noise cleaning setting, compared to conditions with noise cleaning deactivated.   

Conclusions: The majority of participants preferred to have noise cleaning active. Those who did not prefer the noise cleaning algorithm in the laboratory were consistent with this preference and reliably disabled noise cleaning technology in the app. Activating the algorithm had no consistent detrimental effects for speech recognition performance and had reduced listening effort in some cases. Combined, these findings support this noise cleaning algorithm for adolescents, especially if they have access to a smartphone app to manually manipulate noise-cleaning settings.