Children with Hearing Loss Health-Related Quality of Life and Parental Perceptions
Bibliographic record
Abstract
This study aimed to evaluate two objectives: first, the health-related quality of life (HRQoL) and socio-demographic characteristics of children with cochlear implants (CIs) or hearing aids (HAs) on the Kid-KINDLR_children_7-13 questionnaire, and second to analyze parental background factors and the perceptions of their children with CIs or HAs on the Kid_Kiddo-KINDLR_Parents_ 7-17 questionnaire. The data consisted of 89 children with CIs and 63 children with HAs and their 89 parents, respectively. The characteristics of children and the parental factors included demographic and audiological variables. Student’s t-test and one-way ANOVA were used to analyze the two objectives. Children with CIs exhibited a perception of better HRQoL in comparison with children with HAs. Among other differences, children with CIs or HAs and their parents were significantly distinct in the variable Setting (t = 2.921, p < 0.010). Moreover, parents of children with CIs or HAs were significantly different among them in some background factors (i.e., age, socioeconomic status, and learning). Children with CIs and their parents demonstrated a perception of better HRQoL than children with HAs and their parents. These findings added to the existing knowledge about the benefits of CIs for children with hearing loss. Parents of children with CIs noted the significance of social and emotional development as a marker of well-being in their children’s lives.
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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".