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Record W2619054138 · doi:10.3766/jaaa.17007

Evaluation of the Repeatability and Accuracy of the Wideband Real-Ear-to-Coupler Difference

2017· article· en· W2619054138 on OpenAlexaff
Jonathan M. Vaisberg, Paula Folkeard, John Pumford, Philipp Narten, Susan Scollie

Bibliographic record

VenueJournal of the American Academy of Audiology · 2017
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsWestern University
Fundersnot available
KeywordsRepeatabilityAudiologyWidebandAcousticsMedicineMathematicsStatisticsEngineeringElectronic engineeringPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: The real-ear-to-coupler difference (RECD) is an ANSI standardized method for estimating ear canal sound pressure level (SPL) thresholds and assisting in the prediction of real-ear aided responses. It measures the difference in dB between the SPL produced in the ear canal and the SPL produced in an HA-1 2-cc coupler by the same sound source. Recent evidence demonstrates that extended high-frequency bandwidth, beyond the hearing aid bandwidth typically measured, is capable of providing additional clinical benefit. The industry has, in turn, moved toward developing hearing aids and verification equipment capable of producing and measuring extended high-frequency audible output. As a result, a revised RECD procedure conducted using a smaller, 0.4-cc coupler, known as the wideband-RECD (wRECD), has been introduced to facilitate extended high-frequency coupler-based measurements up to 12.5 kHz. PURPOSE: This study aimed to (1) compare test-retest repeatability between the RECD and wRECD and (2) measure absolute agreement between the RECD and wRECD when both are referenced to a common coupler. RESEARCH DESIGN: RECDs and wRECDs were measured bilaterally in adult ears by calculating the dB difference in SPL between the ear canal and coupler responses. Real-ear probe microphone measures were completed twice per ear per participant for both foam-tip and customized earmold couplings using the Audioscan Verifit 1 and Verifit 2 fitting systems, followed by measurements in the respective couplers. STUDY SAMPLE: Twenty-one adults (mean age = 67 yr, range = 19-78) with typical aural anatomy (as determined by measures of impedance and otoscopy) participated in this study, leading to a sample size of 42 ears. DATA COLLECTION AND ANALYSIS: Repeatability within RECD and wRECD was assessed for each coupling configuration using a repeated-measures analysis of variance (ANOVA) with test-retest and frequency as within-participants factors. Repeatability between the RECD and wRECD was assessed within each configuration using a repeated-measures ANOVA with test-retest, frequency, and coupler type as within-participants factors. Agreement between the RECD and wRECD was assessed for each coupling configuration using a repeated-measures ANOVA with RECD value, coupler type, and frequency as within-participants factors. Post hoc comparisons with Bonferroni corrections were used when appropriate to locate the frequencies at which differences occurred. A 3-dB criterion was defined to locate differences of clinical significance. RESULTS: Average absolute test-retest differences were within ±3 dB within each coupler and coupling configuration, and between the RECD and wRECD. The RECD and wRECD were in absolute agreement following HA-1-referenced transforms, with most frequencies agreeing within ±1 dB, except at 0.2 kHz for the earmold, and 0.2-0.25 kHz for the foam tip, where the average RECD exceeded the average wRECD by slightly >3 dB. CONCLUSIONS: Test-retest repeatability of the RECD (up to 8 kHz) and wRECD (up to 12.5 kHz) is acceptable and similar to previously reported data. The RECD and wRECD are referenced to different couplers, but can be rendered comparable with a simple transform, producing values that are in accordance with the ANSI S3.46-2013 standard.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.375
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2017
Admission routes1
Has abstractyes

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