Cochlear Implant Data Logs Predict Children's Receptive Vocabulary.

Objectives: The data logs of Cochlear Nucleus cochlear implant (CI) sound processors show large interindividual variation in children's daily CI use and auditory environments. This study explored whether these differences are associated with differences in the receptive vocabulary of young implanted children. Design: Data of 52 prelingually deaf children, who had received a CI before 3 years of age, were obtained from their clinical records. In total, 73 Peabody Picture Vocabulary tests and CI data logs for 1 year preceding each test were collected. The data logs were used to determine the children's average daily amount of CI use and exposure to speech, speech in noise, noise, music, and quiet. In addition, information was collected about other potential predictors of language abilities, namely gender, age, age at implantation, etiology of deafness, educational placement, and implantation mode (unilateral, bilateral). Model selection with Akaike's information criterion was used to determine which data-logging metrics, other variables, and combinations of both best predict receptive vocabulary scores. Results: The data showed a strong positive association between receptive vocabulary and daily CI use, and a negative association between receptive vocabulary and daily exposure to music. Associations with the data logs' speech and noise metrics were less clear. The most important other variable was educational placement. The best model performance was achieved when data logs and other information were combined. Conclusions: The results emphasize the importance of consistent CI use and a rich auditory environment for the early language development of young CI users. The study also shows that CI data logs capture information about children's environment and CI use that are related to language performance and can help to detect and address problems and improve the auditory rehabilitation after cochlear implantation.