Classification of Hearing Aids Into Feature Profiles Using Hierarchical Latent Class Analysis Applied to a Large Dataset of Hearing Aids.
Simon Lansbergen, Wouter A Dreschler
PMID 33136637WHAT IT FOUND
Nine behind-the-ear and seven in-the-ear feature profiles emerged from a database of 3083 hearing aids, not simply basic or premium.
The profiles describe technical feature combinations, but no evidence shows any profile fits patients better.
Key findings
01The analysis reduced technical hearing aid data to 10 key features: compression, sound processing, noise reduction, expansion, wind noise reduction, impulse reduction, active feedback management, directionality, noise reduction environments, and ear-to-ear communication.
02The model classified 3083 hearing aids into nine behind-the-ear feature profiles and seven in-the-ear feature profiles.
03Brand analysis showed feature profiles were not evenly distributed across brands, and some profiles consisted almost completely of one brand.
STILL TO COME
How it was doneWhat they found
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What it does not show
The study analysed hearing aids, not patients, so it cannot show which device helps a person. The data were only from hearing aids available in the Dutch hearing aid market, so the profiles may not match devices elsewhere. Devices with missing or invalid technical data were removed, and most removed devices came from three brands. The feature domains and grouping were partly subjective, and the authors say the list of features is not complete. The modalities have not been matched to rehabilitation outcomes, so there is no evidence that any modality performs better.
Declared interests
The Heinsius-Houbolt Fund supported part of the work, and the authors declared no conflicts of interest.
The easy way to misread this
Do not read these feature profiles as proof that one hearing aid works better for a patient. The study grouped devices by technical feature levels only, and the authors state the modalities have not been matched to rehabilitation outcomes.