Effects of Age at Cochlear Implantation on Learning and Cognition: A Critical Assessment
Bibliographic record
Abstract
Purpose Age at cochlear implantation frequently is assumed to be a key predictor of pediatric implantation benefits, but outcomes related to learning and cognition appear inconsistent. This critical assessment examines relevant literature in an effort to evaluate the impact of age at implantation in those domains for individuals who received their devices as children. Method We examined 44 peer-reviewed articles from 2003 to 2018 considering age at implantation and conducted statistical analyses regarding its impact on several domains, including literacy, academic achievement, memory, and theory of mind. Results Across 167 assessments in various experiments and conditions, only 21% of the analyses related to age at implantation yielded evidence in favor of earlier implantation, providing greater benefits to academic achievement, learning, or cognition compared to implantation later in childhood. Among studies that considered cognitive processing (e.g., executive function, memory, visual-spatial functioning), over twice as many analyses indicated significant benefits of earlier implantation when it was considered as a discrete rather than a continuous variable. Conclusion Findings raise methodological, practical, and theoretical questions concerning how "early" is defined in studies concerning early cochlear implantation, the impact of confounding factors, and the use of nonstandard outcome measures. The present results and convergent findings from other studies are discussed in terms of the larger range of variables that need to be considered in evaluating the benefits of cochlear implantation and question the utility of considering age at implantation as a "gold standard" with regard to evaluating long-term outcomes of the procedure as a medical treatment/intervention for hearing loss. Supplemental Material https://doi.org/10.23641/asha.8323625.
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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 | 0.035 | 0.182 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.023 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".