Predicting Individual Hearing-Aid Preference From Self-Reported Listening Experiences in Daily Life.

Objectives: The study compared the utility of two approaches for collecting real-world listening experiences to predict hearing-aid preference: a retrospective questionnaire (Speech, Spatial, and Qualities of Hearing Scale [SSQ]) and in-situ Ecological Momentary Assessment (EMA). The rationale being that each approach likely provides different and yet complementary information. In addition, it was examined how self-reported listening activity and hearing-aid data-logging can augment EMAs for individualized and contextualized hearing outcome assessments.

Evaluating Real-World Benefits of Hearing Aids With Deep Neural Network-Based Noise Reduction: An Ecological Momentary Assessment Study.

Purpose: Noise reduction technologies in hearing aids provide benefits under controlled conditions. However, differences in their real-life effectiveness are not established. We propose that a deep neural network (DNN)-based noise reduction system trained on naturalistic sound environments will provide different real-life benefits compared to traditional systems.

Short-Term Pediatric Acclimatization to Adaptive Hearing Aid Technology.

Purpose This exploratory study assessed the perceptual, cognitive, and academic learning effects of an adaptive, integrated, directionality, and noise reduction hearing aid program in pediatric users. Method Fifteen pediatric hearing aid users (6-12 years old) received new bilateral, individually fitted Oticon Opn hearing aids programmed with OpenSound Navigator (OSN) processing. Word recognition in noise, sentence repetition in quiet, nonword repetition, vocabulary learning, selective attention, executive function, memory, and reading and mathematical abilities were measured within 1 week of the initial hearing aid fitting and 2 months post fit.