MétaCan
Menu
Back to cohort
Record W4399141376 · doi:10.1080/14670100.2024.2341208

Health literacy of patients eligible for cochlear implants

2024· article· en· W4399141376 on OpenAlexaff
Dorsa Mavedatnia, Li Wang, Alex Kiss, Eric F Monteiro, Vincent Lin

Bibliographic record

VenueCochlear Implants International · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsSunnybrook Health Science CentreSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsHealth literacyMedicineAudiologyCochlear implantationLiteracyCochlear implantHearing lossPhysical therapyHealth carePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Hearing loss is known to be an independent risk factor for inadequate health literacy. The objective of this study was to assess the level of health literacy among patients undergoing cochlear implantation to determine areas for improvement in delivery of patient information. METHODS: A cross-sectional survey was conducted at the otology-neurotology clinic at Sunnybrook Health Sciences Centre. Patients eligible for cochlear implantation completed two health literacy screening tools: The Short Test of Functional Health Literacy in Adults (S-TOFHLA) and Brief Health Literacy Screen (BHLS). RESULTS: Thirty seven patients were included (41% female, 59% male, mean age: 55 years). Most patients had adequate health literacy through BHLS (76%) and S-TOFHLA (98%) scoring. Over 80% of patients were not able to correctly recount all the operative risks associated with cochlear implant surgery and one third of patients did not correctly recount any risks associated with a cochlear implant surgery. Female sex was associated with higher scores (p=0.03) and low income (<$35,000) was associated with lower scores (p=0.05). CONCLUSION: Patients eligible for cochlear implants have adequate health literacy, but most are not able to recount operative risks. Educational tools are required to improve patient retention, understand, and perioperative health information delivery.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.045
GPT teacher head0.502
Teacher spread0.457 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCochlear Implants InternationalSame topicHealth Literacy and Information AccessibilityFrench-language works237,207