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Record W4416528278 · doi:10.1016/j.heares.2025.109482

Validating and refining a psychoacoustic test to diagnose hyperacusis

2025· article· en· W4416528278 on OpenAlexafffund
Philippe Fournier, Pierre H Bourez, A. Cote, Nicolas Detroy, Claudia Côté, Arnaud Noreña

Bibliographic record

VenueHearing Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsCentres Intégré Universitaires de Santé et de Services SociauxInternational Laboratory for Brain, Music and Sound ResearchCentre for Interdisciplinary Research in Rehabilitation
FundersFonds de Recherche du Québec - SantéAgence Nationale de la RechercheInstitut de Réadaptation en Déficience Physique de QuébecRéseau Provincial de Recherche en Adaptation-RéadaptationUniversité LavalAix-Marseille Université
KeywordsHyperacusisLoudnessPsychoacousticsTest (biology)PerceptionAuditory perceptionTinnitus

Abstract

fetched live from OpenAlex

ABSTRACT Decreased sound tolerance refers to conditions like hyperacusis and misophonia, in which everyday sounds may provoke discomfort or distress. Hyperacusis is characterized by exaggerated loudness perception and aversive reactions to moderate to loud sounds, often leading to significant impairment. Despite its estimated prevalence of 10–15%, no objective clinical test exists. Current assessment relies on interviews, questionnaires, and loudness discomfort levels (LDLs), which lack reliability and ecological validity. Recent work has shown that pleasantness ratings of natural sounds can differentiate individuals with hyperacusis from controls. A subset of seven natural sounds, termed Core Discriminant Sounds (CDS hyper ), was identified post-hoc as particularly effective, yielding 81% sensitivity and 88% specificity in prior lab-based testing. A similar approach for misophonia identified ten distinct trigger sounds (CDS miso ). This study aimed to validate a tablet-based version of the CDS test to diagnose hyperacusis prospectively. Forty-nine participants (20 with hyperacusis, 29 controls) completed the test that presented randomly CDS hyper and CDS miso sounds at 60, 70, and 80 dBA. Participants rated each sound presentation on visual analog scales for pleasantness and loudness. Hyperacusis was defined by clinical complaints, Hyperacusis Questionnaire scores (≥22), and LDLs (≤77 dB HL). Results showed that individuals with hyperacusis rated CDS hyper sounds as significantly less pleasant (means score of 39 vs 25 for hyperacusis vs controls, p = .002, η² = .185) and louder (means score of 71 vs 63 for hyperacusis vs controls, p = .024, η² = .104) than controls. No group differences emerged for misophonia trigger sounds (CDS miso sounds). The sensitivity and specificity for the combined CDS hyper scores of pleasantness and loudness at detecting hyperacusis were 90% and 69%, respectively. These findings validate the tablet-based test as an efficient, ecologically valid tool for diagnosing hyperacusis.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.275
GPT teacher head0.625
Teacher spread0.349 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes2
Has abstractyes

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