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Record W4415683869 · doi:10.1097/aud.0000000000001713

Validation and Preference-Based Scoring of the York Binaural Hearing-Related Quality of Life Questionnaire for Young People

2025· article· en· W4415683869 on OpenAlexaff
Adam J. Pedley, Sarah Somerset, Deborah Vickers, Dan Jiang, Pádraig T. Kitterick

Bibliographic record

VenueEar and Hearing · 2025
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsActive listeningQuality of life (healthcare)Sound qualityMeasure (data warehouse)Hearing aidBinaural recordingPsychometrics

Abstract

fetched live from OpenAlex

OBJECTIVES: The York Binaural Hearing-Related Quality of Life questionnaire for Young People (YBHRQL-Y) is a 3-item measure of hearing-related quality of life devised specifically for use with young people (children aged 8 to 16 years old) with hearing loss. This research had three objectives: (1) to assign numerical values where a higher value corresponds to better perceived overall health status ("health utility weights") to each of 27 unique combinations of difficulties with speech understanding, sound localization, and listening effort ("hearing health states"); (2) to assess its validity and reproducibility when used with young people with hearing loss; (3) to assess the feasibility of a proxy version designed to be completed by the parents/guardians of young people with hearing loss. DESIGN: Health utility weights were obtained by conducting time trade-off interviews with a cross-sectional sample of 155 young adults, aged 18 to 24 years old, recruited from social media and UK universities. To assess validity and reproducibility, the YBHRQL-Y and other established instruments measuring functional hearing and hearing-related quality of life in children were administered to young people with hearing loss at two time points, 2 wk apart. In total, 71 children aged 8 to 16 yr old with at least a severe hearing loss took part and were recruited from social media, relevant charities, and support groups in the United Kingdom. The feasibility of obtaining information about the binaural hearing-related quality of life of young people with hearing loss indirectly was assessed by administering a proxy version of the YBHRQL-Y to the parents or guardians of the young people who participated in the research. A total of 71 parents or guardians were recruited from social media, relevant charities, and support groups in the United Kingdom. RESULTS: The health utility weights elicited from young adults varied monotonically with the level of hearing-related impact described on each of the three dimensions of the YBHRQL-Y, such that the greater the degree of hearing-related impact, the poorer the corresponding health state was judged to be by the respondents. Convergent validity analyses suggested that the domains of the YBHRQL-Y measure the intended constructs and the overall measure relates to the respondent's health-related quality of life. Test-retest analyses suggested it was reliable and showed good agreement between administrations. Pairwise analysis of responses from the young person with hearing loss and those of their parent/guardian suggested that the proxy measure had poor reliability and poor agreement with the measure administered directly to the young person with hearing loss. CONCLUSIONS: The YBHRQL-Y is a valid and reliable measure of hearing-related quality of life when administered directly to a young person aged 8 to 16 with at least a severe hearing loss. An individual's preference-based score, derived from the preferences of young adults, successfully integrates information about binaural-related hearing across the domains of speech understanding, sound localization, and listening effort. The combination of brief age-appropriate questions, good psychometric performance across time, and a preference-based scoring method makes the YBHRQL-Y a straightforward means to assess hearing-related quality of life in young people with hearing loss.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.237
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.095
GPT teacher head0.317
Teacher spread0.222 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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