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Record W2554848255 · doi:10.3766/jaaa.15138

Factors Affecting Daily Cochlear Implant Use in Children: Datalogging Evidence

2016· article· en· W2554848255 on OpenAlexaff
Vijayalakshmi Easwar, Joseph S. Sanfilippo, Blake C. Papsin, Karen A. Gordon

Bibliographic record

VenueJournal of the American Academy of Audiology · 2016
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAudiologyActive listeningMedicineCochlear implantHearing lossLimitingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Children with profound hearing loss can gain access to sound through cochlear implants (CIs), but these devices must be worn consistently to promote auditory development. Although subjective parent reports have identified several factors limiting long-term CI use in children, it is also important to understand the day-to-day issues which may preclude consistent device use. In the present study, objective measures gathered through datalogging software were used to quantify the following in children: (1) number of hours of CI use per day, (2) practical concerns including repeated disconnections between the external transmission coil and the internal device (termed "coil-offs"), and (3) listening environments experienced during daily use. PURPOSE: This study aimed to (1) objectively measure daily CI use and factors influencing consistent device use in children using one or two CIs and (2) evaluate the intensity levels and types of listening environments children are exposed to during daily CI use. RESEARCH DESIGN: Retrospective analysis. STUDY SAMPLE: Measures of daily CI use were obtained from 146 pediatric users of Cochlear Nucleus 6 speech processors. The sample included 5 unilateral, 40 bimodal, and 101 bilateral CI users (77 simultaneously and 24 sequentially implanted). DATA COLLECTION AND ANALYSIS: Daily CI use, duration, and frequency of coil-offs per day, and the time spent in multiple intensity ranges and environment types were extracted from the datalog saved during clinic appointments. Multiple regression analyses were completed to predict daily CI use based on child-related demographic variables, and to evaluate the effects of age on coil-offs and environment acoustics. RESULTS: Children used their CIs for 9.86 ± 3.43 hr on average on a daily basis, with use exceeding 9 hr per day in ∼64% of the children. Daily CI use reduced significantly with increasing durations of coil-off (p = 0.027) and increased significantly with longer CI experience (p < 0.001) and pre-CI acoustic experience (p < 0.001), when controlled for the child's age. Total time in sound (sum of CI and pre-CI experience) was positively correlated with CI use (r = 0.72, p < 0.001). Longer durations of coil-off were associated with higher frequency of coil-offs (p < 0.001). The frequency of coil-offs ranged from 0.99 to 594.10 times per day and decreased significantly with age (p < 0.001). Daily CI use and frequency of coil-offs did not vary significantly across known etiologies. Listening environments of all children typically ranged between 50 and 70 dBA. Children of all ages were exposed to speech in noisy environments. Environment classified as "music" was identified more often in younger children. CONCLUSIONS: The majority of children use their CIs consistently, even during the first year of implantation. The frequency of coil-offs is a practical challenge in infants and young children, and demonstrates the need for improved coil retention methods for pediatric use. Longer hearing experience and shorter coil-off time facilitates consistent CI use. Children are listening to speech in noisy environments most often, thereby indicating a need for better access to binaural cues, signal processing, and stimulation strategies to aid listening. Study findings could be useful in parent counseling of young and/or new CI users.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.078
GPT teacher head0.344
Teacher spread0.266 · 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

Citations55
Published2016
Admission routes1
Has abstractyes

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