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Record W7117654653 · doi:10.1016/j.heares.2025.109522

Anxiety and depression among Canadian undergraduates with decreased sound tolerance

2025· article· en· W7117654653 on OpenAlexafffundabout
Carter M. Smith, Natalia Van Esch, Nichole E. Scheerer

Bibliographic record

VenueHearing Research · 2025
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsWilfrid Laurier University
FundersWilfrid Laurier University
KeywordsAnxietyMental healthDepression (economics)Sound (geography)Face (sociological concept)

Abstract

fetched live from OpenAlex

Decreased sound tolerance (DST) is an encompassing term for conditions marked by a reduced tolerance to everyday sounds. Misophonia, sensitivity to specific trigger sounds which cue aversive responses, is one DST subtype. Hyperacusis, another DST subtype, occurs when people are irritated by general sounds that are not bothersome to others. Research suggests that those with DST face heightened mental health challenges. Psychometrically validated measures aligned with the recent misophonia consensus definition have not assessed the relationship between misophonia and mental health. There is also a complete dearth of DST-mental health research in Canadian universities. Here, 2095 Canadian undergraduate students completed DST and mental health questionnaires. We explored the relationship between anxiety and depression and DST. We found strong, positive correlations between DST symptoms and mental health difficulties. These findings highlight DST's detrimental effects and the need for future research on strategies for managing and treating DST in post-secondary institutions.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.023
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.078
GPT teacher head0.357
Teacher spread0.280 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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