Evidence map›Paper›PMID 32693613›Full record

ArticleAmerican journal of audiology2020

Common Configurations of Real-Ear Aided Response Targets Prescribed by NAL-NL2 for Older Adults With Mild-to-Moderate Hearing Loss.

Justin Jensen, Dhruv Vyas, Dana Urbanski, Harinath Garudadri, Octav Chipara, Yu-Hsiang Wu

Open access · greenAbstract read
In one paragraph

Article in American journal of audiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Justin JensenDepartment of Communication Sciences and Disorders, The University of Iowa, Iowa City.
Dhruv VyasDepartment of Computer Science, The University of Iowa, Iowa City.
Dana UrbanskiDepartment of Communication Sciences and Disorders, The University of Iowa, Iowa City.
Harinath GarudadriQualcomm Institute, University of California San Diego.
Octav ChiparaDepartment of Computer Science, The University of Iowa, Iowa City.
Yu-Hsiang WuDepartment of Communication Sciences and Disorders, The University of Iowa, Iowa City.
University of Iowa · USUniversity of California San Diego · US

Funding

Quantifying Physical and Social Isolation, and Assessing Perceived LonelinessR01DC015436 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GARUDADRI, HARINATH · 2016 to 2020
$2.4M
Self fitting of Amplification: Methodology and CandidacyR33DC015046 · NIDCD · SAN DIEGO STATE UNIVERSITY · PI GARUDADRI, HARINATH, MACKERSIE, CAROL L · 2017 to 2020
$2.0M
An Open-source Speech Processing Platform (OSP) for Research on Hearing Loss and Related DisordersR44DC020406 · NIDCD · NADI LLC · PI GARUDADRI, HARINATH · 2022 to 2023
$2.0M
Self fitting of Amplification: Methodology and CandidacyR21DC015046 · NIDCD · SAN DIEGO STATE UNIVERSITY · PI GARUDADRI, HARINATH, MACKERSIE, CAROL L · 2016 to 2016
$222k
NIDCD NIH HHS R01 DC015436NIDCD NIH HHS R21 DC015046NIDCD NIH HHS R33 DC015046NIDCD NIH HHS R44 DC020406
6 · The paper itself

Abstract

Purpose This study investigates common real-ear aided response (REAR) configurations prescribed by the NAL-NL2 algorithm for older adults with hearing loss. Method A data set that is representative of the older adult U.S. population with mild-to-moderate sensorineural hearing loss was constructed from the audiometric data of 934 adults (aged 55-85 years) from the National Health and Nutrition Examination Survey years 1999-2012. Two clustering approaches were implemented to generate common REAR configurations for eight frequencies (0.25, 0.5, 1, 2, 3, 4, 6, and 8 kHz) at three input levels (55, 65, and 75 dB SPL). (a) In the REAR-based clustering approach, the National Health and Nutrition Examination Survey audiograms were first converted to REAR targets and then clustered to generate common REAR configurations. (b) In the audiogram-based clustering approach, the audiograms were first clustered into common hearing loss profiles and then converted to REAR configurations. The trade-off between the number of available REAR configurations and the percentage of the U.S. population whose hearing loss could be fit by at least one of them (i.e., percent coverage) was evaluated. Hearing loss fit was defined as less than ± 5-dB difference between an individual's REAR targets and those of the clustered REAR configuration. Results Percent coverage increases with the number of available REAR configurations, with four configurations resulting in 75% population coverage. Overall, REAR-based clustering yielded 5 percentage points better coverage on average compared to audiogram-based clustering. Conclusions The common REAR configurations can be used for programming the gain frequency responses in preconfigured over-the-counter hearing aids and provide clinically appropriate amplification settings for older adults with mild-to-moderate hearing loss.

Indexed as

Hearing AidsSignal Processing, Computer-AssistedAgedAged, 80 and overCorrection of Hearing ImpairmentEquipment DesignFemaleHearing Loss, SensorineuralHumansMaleMiddle AgedSeverity of Illness Index

Identifiers

PMID32693613
PMCPMC7842845
OpenAlexW3045233422

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.