Evidence map›Paper›PMID 25669257›Full record

ArticleThe Journal of the Acoustical Society of America2013

Integrating cognitive and peripheral factors in predicting hearing-aid processing effectiveness.

James M Kates, Kathryn H Arehart, Pamela E Souza

Abstract readComparative Study
In one paragraph

Article in The Journal of the Acoustical Society of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Relationships Between Auditory Processing and Cognitive Abilities in Adults: A Systematic Review.Journal of speech, language, and hearing research : JSLHR · 2024
    Pooled it
  2. Trial
  3. Review
  4. Review
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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

3 authors.

James M KatesDepartment of Speech Language and Hearing Sciences, University of Colorado, Boulder, Colorado 80309.
Kathryn H ArehartDepartment of Speech Language and Hearing Sciences, University of Colorado, Boulder, Colorado 80309.
Pamela E SouzaDepartment of Communication Sciences and Disorders and Knowles Hearing Center, Northwestern University, Evanston, Illinois 60201.

Funding

Characterizing Variability in Hearing Aid Outcomes Among Older AdultsR01DC012289 · NIDCD · NORTHWESTERN UNIVERSITY · PI SOUZA, PAMELA E. · 2012 to 2021
$3.7M
NIDCD NIH HHS R01 DC012289
6 · The paper itself

Abstract

Individual factors beyond the audiogram, such as age and cognitive abilities, can influence speech intelligibility and speech quality judgments. This paper develops a neural network framework for combining multiple subject factors into a single model that predicts speech intelligibility and quality for a nonlinear hearing-aid processing strategy. The nonlinear processing approach used in the paper is frequency compression, which is intended to improve the audibility of high-frequency speech sounds by shifting them to lower frequency regions where listeners with high-frequency loss have better hearing thresholds. An ensemble averaging approach is used for the neural network to avoid the problems associated with overfitting. Models are developed for two subject groups, one having nearly normal hearing and the other mild-to-moderate sloping losses.

Indexed as

CognitionHearing AidsSpeech IntelligibilitySpeech PerceptionAcoustic StimulationAgedAged, 80 and overAudiometry, SpeechAuditory ThresholdElectric StimulationEquipment DesignFemaleHearing LossHumansMiddle AgedNeural Networks, Computer

Identifiers

PMID25669257
PMCPMC3874061

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.