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Record W2276617617 · doi:10.1177/0003489415592000

Decisional Conflict in Parents Considering Bone-Anchored Hearing Devices in Children With Unilateral Aural Atresia

2015· article· en· W2276617617 on OpenAlexaff
M. Elise Graham, Rebecca Haworth, Jill Chorney, Manohar Bance, Paul Hong

Bibliographic record

VenueAnnals of Otology Rhinology & Laryngology · 2015
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsAudiologyAtresiaPsychologyMedicineDentistryAcousticsAnatomyPhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: The benefits of bone-anchored hearing devices (BAHD) in children with unilateral aural atresia are controversial. We sought to determine whether there is parental decisional conflict surrounding elective placement of BAHD for this indication. METHODS: Caregivers of pediatric patients with unilateral aural atresia and normal contralateral ear undergoing percutaneous BAHD consultation were enrolled. All consultations were carried out by one pediatric otolaryngologist in a consistent manner. After consultation, the participants completed a demographics form and the Decisional Conflict Scale (DCS) questionnaire. RESULTS: Twenty-three caregivers of 15 male (65.2%) and 8 female (34.8%) children (mean age 5.65 years) participated. The overall median DCS score was 15.63 (standard error = 4.21). Significant decisional conflict (DCS score ≥ 25) was found in 10 participants (43.5%). The median DCS score in the group choosing surgery was 5.47, and it was 23.44 in those who did not choose surgery (Mann-Whitney U = 39, Z = -1.391, P = .164). The median DCS score for mothers and fathers was 25 and 3.91, respectively. CONCLUSION: Many parents experienced significant decisional conflict when considering percutaneous BAHD surgery in children with unilateral aural atresia in our study population. Future research should explore the impact of decisional conflict on health outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.097
GPT teacher head0.338
Teacher spread0.240 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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