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Record W2323379792 · doi:10.3766/jaaa.25.10.9

The Ling 6(HL) Test: Typical Pediatric Performance Data and Clinical Use Evaluation

2014· article· en· W2323379792 on OpenAlexaff
Danielle Glista, Susan Scollie, Sheila Moodie, Vijayalakshmi Easwar

Bibliographic record

VenueJournal of the American Academy of Audiology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsAudiologyHearing aidMedicineConfidence intervalHearing lossTest (biology)Sensorineural hearing lossInterpretabilityData collectionComputer scienceStatisticsArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: The Ling 6(HL) test offers a calibrated version of naturally produced speech sounds in dB HL for evaluation of detection thresholds. Aided performance has been previously characterized in adults. PURPOSE: The purpose of this work was to evaluate and refine the Ling 6(HL) test for use in pediatric hearing aid outcome measurement. RESEARCH DESIGN: This work is presented across two studies incorporating an integrated knowledge translation approach in the characterization of normative and typical performance, and in the evaluation of clinical feasibility, utility, acceptability, and implementation. STUDY SAMPLE: A total of 57 children, 28 normally hearing and 29 with binaural sensorineural hearing loss, were included in Study 1. Children wore their own hearing aids fitted using Desired Sensation Level v5.0. Nine clinicians from The Network of Pediatric Audiologists participated in Study 2. DATA COLLECTION AND ANALYSIS: A CD-based test format was used in the collection of unaided and aided detection thresholds in laboratory and clinical settings; thresholds were measured clinically as part of routine clinical care. Confidence intervals were derived to characterize normal performance and typical aided performance according to hearing loss severity. Unaided-aided performance was analyzed using a repeated-measures analysis of variance. The audiologists completed an online questionnaire evaluating the quality, feasibility/executability, utility/comparative value/relative advantage, acceptability/applicability, and interpretability, in addition to recommendation and general comments sections. RESULTS: Ling 6(HL) thresholds were reliably measured with children 3-18 yr old. Normative and typical performance ranges were translated into a scoring tool for use in pediatric outcome measurement. In general, questionnaire respondents generally agreed that the Ling 6(HL) test was a high-quality outcome evaluation tool that can be implemented successfully in clinical settings. CONCLUSIONS: By actively collaborating with pediatric audiologists and using an integrated knowledge translation framework, this work supported the creation of an evidence-based clinical tool that has the potential to be implemented in, and useful to, clinical practice. More research is needed to characterize performance in alternative listening conditions to facilitate use with infants, for example. Future efforts focused on monitoring the use of the Ling 6(HL) test in daily clinical practice may help describe whether clinical use has been maintained across time and if any additional adaptations are necessary to facilitate clinical uptake.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.128
GPT teacher head0.417
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations31
Published2014
Admission routes1
Has abstractyes

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