Health related quality of life in adolescent cochlear implant users
Bibliographic record
Abstract
Objective: Children with significant hearing loss (HL) are at risk for lower self-esteem and lower perceived quality of life (QoL). This study examined how self-reported QoL of adolescents cochlear implant (CI) users compared to that of adolescents with normal hearing, and examined if factors such as socioeconomic status (SES) and communication methodology affect QoL and speech recognition.Methods: Forty-three adolescent CI users completed a 34-item questionnaire that included questions adapted from the QoL of Deaf or Hard-of-Hearing Youth questionnaire (Seattle Quality of Life Group SEAQOL. 2010 Quality of life of deaf or hard-of-hearing youth (YQOL-DHH). Seattle, Washington) and from the Kidscreen-10 Index (The KIDSCREEN Group, Europe, 2006, the KIDSCREEN questionnaires - quality of life questionnaires for children and adolescents handbook. Lengerich: Pabst Science Publishers. All subjects received their first CI prior to the age of 5, and ranged in age from 10–17 years at the time of survey completion.Results: Adolescents with CIs demonstrated self-reported QoL scores similar to children with normal hearing. Lower SES and communication mode appear to influence speech recognition, and also appear to impact self-reported QoL in different ways.Conclusions: Examination of communication outcomes, along with other factors that influence QoL, such as SES, will help clinicians identify children at risk for low QoL. Such identification will help generate appropriate referrals to enhance QoL in adolescent CI users.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".