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Record W3025282211 · doi:10.1001/jamaoto.2020.0674

Health-Related Quality of Life Changes Associated With Hearing Loss

2020· review· en· W3025282211 on OpenAlexaff
Peter R. Dixon, David Feeny, George Tomlinson, Sharon L. Cushing, Joseph M. Chen, Murray Krahn

Bibliographic record

VenueJAMA Otolaryngology–Head & Neck Surgery · 2020
Typereview
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreHospital for Sick ChildrenMcMaster UniversityUniversity Health NetworkUniversity of TorontoHamilton Utilities CorporationToronto Public Health
Fundersnot available
KeywordsHearing lossQuality of life (healthcare)MedicineReferralMEDLINEHearing aidAudiologyRehabilitationMinimum Data SetTime-trade-offGerontologyFamily medicinePhysical therapyNursing

Abstract

fetched live from OpenAlex

Importance: Utility is a single-value, preference-based measure of health-related quality of life that represents the desirability of a health state relative to being dead or in perfect health. Clinical, funding, and policy decisions rely on measured changes in utility. The benefit of hearing loss treatments may be underestimated because existing utility measures fail to capture important changes in quality of life associated with hearing loss. Objective: To develop a comprehensive profile of items that describe how quality of life is associated with hearing loss and its treatments that can be used to generate hearing-related quality of life measures, including a novel utility measure. Design, Setting, and Participants: This qualitative study, performed from August 1, 2018, to August 1, 2019, in tertiary referral centers, comprised a systematic literature review, focus groups, and semistructured interviews. The systematic review evaluated studies published from 1982 to August 1, 2018. Focus groups included 8 clinical experts experienced in the measurement, diagnosis, treatment, and rehabilitation of hearing loss. Semistructured interviews included 26 adults with hearing loss recruited from an institutional data set and outpatient hearing aid and otology clinics using stratified convenience sampling to include individuals of diverse ages, urban and rural residency, causes of hearing loss, severity of hearing loss, and treatment experience. Main Outcomes and Measures: A set of items and subdomains that collectively describe the association of hearing loss with health-related quality of life. Results: The literature search yielded 2779 articles from the MEDLINE, Embase, Cochrane, PsycINFO, and CINAHL databases. Forty-five studies including 1036 individuals (age range, 18-84 years) were included. The focus group included 4 audiologists and 4 otologists. Hour-long semistructured interviews were conducted with 26 individuals (13 women; median age, 54 years; range, 25-83 years) with a broad range of hearing loss causes, configurations, and severities. From all 3 sources, a total of 125 items were generated and organized into 29 subdomains derived from the World Health Organization's International Classification of Functioning, Disability and Health. Conclusions and Relevance: The association of hearing loss with quality of life is multidimensional and includes subdomains that are not considered in the estimation of health utility by existing utility measures. The presented comprehensive profile of items can be used to generate or evaluate measures of hearing-related quality of life, including utility measures.

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)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.135
GPT teacher head0.349
Teacher spread0.214 · 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 designOther design
Domainnot available
GenreReview

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

Citations85
Published2020
Admission routes1
Has abstractyes

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