Cochlear Implantation Among Deaf Children With Additional Disabilities: Parental Perceptions of Benefits, Challenges, and Service Provision
Bibliographic record
Abstract
Although increasing numbers of children with additional disabilities are receiving cochlear implants (CIs), little is known about family perspectives of the benefits and the challenges of cochlear implantation in this pediatric population. This study examines perceptions among parents of deaf children with additional disabilities regarding satisfaction with service provision, benefits, and challenges of the CI process. This was a mixed-methods study, which included a survey and interviews. Twenty-three families of deaf children with additional disabilities participated in this study, and 17 of these parents participated in in-depth interviews regarding their child's experience with the CI, including benefits and challenges. Interviews were analyzed through inductive thematic analysis. Parent-perceived benefits of cochlear implantation included children's improved sound awareness, communication skills, and greater well-being compared to preimplantation status. However, the majority of families felt that they and their children were not receiving enough services. Major challenges included managing funding; coping with limited availability of specialized services, particularly in rural areas; and continuing concerns about the child's communication, social skills, and academic performance. Results suggest that children with additional disabilities benefit from CIs, but they and their families also face unique challenges that professionals should consider when working with these families.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".