Can Age at Cochlear Implantation Predict Learning and Cognitive Abilities?
Bibliographic record
Abstract
Research over the past three decades has demonstrated clear benefits of lowering the age of cochlear implantation in children with prelingual deafness. The earlier the better argument is based on the critical period hypothesis that suggests the existence of an early, optimal timing for language learning.1 A period of auditory deprivation leads to decreased cortical plasticity over time, with effects on cognitive and linguistic development.2 Thus, it is reasonable to hypothesize that when children with severe to profound hearing loss are provided with the earliest possible access to auditory input via cochlear implantation, neurophysiological development will normalize, and language and cognition development will be facilitated. Age at implantation is viewed as a key factor for predicting speech and language outcomes in pediatric cochlear implant (CI) users.3,4 However, personal, familial, and time-related factors, such as the duration of experience with the implant, have also been reported to be potential factors of influence.5,6 More importantly, little is known about the possible effects of age at implantation on abilities related to language, such as cognitive processing (e.g., memory, problem-solving, theory of mind) and academic outcomes (e.g., reading, mathematics). For example, numerous studies involving secondary and postsecondary cohorts of CI users have shown that the use of a CI was not strongly associated with academic outcomes.7-10 Research to date has not offered definitive answers regarding the effects of age at cochlear implantation on cognition and learning abilities of individuals who received CIs as children. Thus, it was important to conduct an analysis of relevant literature published in the past 15 years regarding the impact of age at implantation on abilities that both underlie language and are supported by it.shutterstock/Kalah_R, cochlear implant, child health, hearing loss.METHODS We conducted searches in diverse and relevant journals and databases to identify research articles on the academic outcomes and other aspects of cognitive processing. The search was limited to peer-reviewed articles that explicitly addressed age at implantation as a variable of interest and provided statistical analyses. The search process resulted in a set of 44 empirical studies published between 2003 and 2018. Although the various methodologies and analyses among the different studies carried significant caveats, they appeared to represent the current state-of-the-art research on CI outcomes. RESULTS Academic outcomes. Eighteen studies included 40 assessments of the effect of age at implantation on reading abilities and reading strategies, reading comprehension, spelling, phonological awareness, and overall academic achievement. Most of the participants were tested between the ages of 8 and 16. Sample sizes ranged from eight to 181 participants with CIs. Mean age at implantation among participant groups ranged from 1.22 to 8.66 years. Results showed that only about half (19) of the analyses (48%) yielded statistically significant results, thus suggesting that age at implantation is not a consistent predictor of literacy and academic outcomes. Overall, results indicated that the association between earlier implantation and better academic achievement is modest. Cognitive processing. Studies that examined cognitive processes focused on general cognitive ability and memory, executive function, theory of mind, verbal cognitive skills (e.g., metaphor comprehension), and sequential learning. Sample sizes ranged from eight to 72 participants with CIs. The age range at the time of testing went from 3 years old to college age. Mean age at implantation among the groups of participants ranged from 1.67 to 7.2 years old. Most of the participants were tested between the ages of 8 and 14. The 24 reviewed studies yielded significant results in only 16 of 127 assessments (13%) that examined the extent to which age at implantation influences cognitive processing. Taken together, the results of this set of studies suggested that, consistent with evidence from studies that examined literacy and academic achievement, age at implantation is not a strong predictor of later cognitive processing, at least in the domains that were assessed in the reviewed studies. Two main findings emerged from empirical results in the 44 studies. First, across the various assessment tasks and heterogeneous groups of participants, there was a total of 167 assessments concerning the effects of age at implantation. Of those 167 assessments, only 35 (21%) resulted in statistically significant effects, indicating the benefits of early implantation. Duration of implant use was reported in many studies, but we were not able to draw any firm conclusion beyond the possibility that confounds with duration of CI use may be problematic when considering the impact of age at implantation. The second main finding is related to the way in which studies dealt with age at implantation as a variable in the statistical analyses. The treatment of age at implantation as a continuous or discrete variable had very little impact on academic achievement results. However, in studies that examined cognitive abilities, significant effects were found more often when age at implantation was treated as a discrete rather than continuous variable. This pattern of findings suggests that age at implantation is an inconsistent predictor of both medium- and long-term outcomes with regard to learning and cognition. Nonetheless, there should be no doubt that, broadly speaking, early cochlear implantation is beneficial and does carry predictive value on cognitive and linguistic achievement, as well as other developmental domains. For example, early cochlear implantation has been shown to improve quality of life11 and self-esteem.12 In this review of the evidence, the methods, designs, tasks, and analyses were highly heterogeneous. In addition, both chronological age and duration of CI use were wide-ranging among the set of reviewed studies. Clearly, these factors, among others, could contribute to the observed outcomes. Beyond methodological and validity issues, this review raises a concern about the relative lack of research on medium- and long-term outcomes of cochlear implantation not only in the domains of learning and cognition but also in other areas of development. Future research focusing on the influence of age at implantation should consider child-, family-, and environment-related factors that can influence the outcomes of cochlear implantation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".