Factors associated with “language gaps” among children with cochlear implants Susan Wiley, J Meinzen-Derr, S Grether, H Barnard, D Choo, J Hibner, L Smith

Background Language skills are highly correlated with academic, occupational, and social success Language “gaps” can impart challenges in academics, social-emotional functioning vocational opportunities, and subsequent earning potential

Background Relatively large numbers of children who are DHH struggle with significantly lower language levels disproportionate to their scores on nonverbal cognitive assessments These lags in early language can have a larger impact through the school years as the language demands increase, irrespective of hearing loss severity

Background Despite early identification and intervention as well as the positive impact of technology, language levels continue to hover in average to low average range for many –Expect 50% have scores >100 and 35% scores >115 Language scores are often used as a “target” –Do not account for an individual’s capability

Objectives of Larger Study Determine the extent to which nonverbal cognitive IQ (NVIQ) explains the divergence between language level and cognitive level Determine specific audiologic features that impact the divergence between language and cognitive level among children with cognitive disabilities Characterize the language-based interventions for children with hearing loss and cognitive disabilities.

Objective of Presented Work Determine factors associated with an underperformance of language among children with cochlear implants

Eligibility of overall study Enrolled 93 children, congenital permanent bilateral hearing loss Ages 3 – 6 years Nonverbal IQ >40 Enrolled hearing children with below average Nonverbal IQ Exclusions: Autism spectrum disorders, unable to complete standardized assessments 41 children with cochlear implants

Eligibility Balanced regarding degree of hearing loss and age 3-6 Years Bilateral hearing loss prelingual Nonverbal IQ >40 NVIQ NVIQ >80

Assessment Tools Language Assessment: –Preschool Language Scales -5 Neurocognitive Assessment: –Leiter International Performance Scale-R, Behavioral Rating Inventory of Executive Function Functional Assessment –Pediatric Evaluation of Disability Inventory –Vineland Adaptive Behavior Scales Detailed family questionnaire and medical chart review

Language Performance LANGUAGE:COGNITIVE RATIO IQ = 100LANGUAGE = 80 80/100 or 0.80 Defined as language abilities relative to cognitive abilities Receptive Language standard score Nonverbal IQ standard score

Statistical Analysis Bivariate analysis occurred between each outcome variable (absolute language scores and the ratio of language level to NVIQ) The relationship between continuous values of NVIQ and other factors was investigated using Pearson correlation with continuous variables and analysis of variance (ANOVA) or t-test for categorical variables We constructed multivariable general linear models to assess the amount of variability (using the coefficient of determination or R2) in outcomes explained by NVIQ

Characteristics CI n=41 HA n=49 Mean Age of study (mos)58.5 (13)56.7 (14.6) Etiology of HL unknown44%49% Duration of Implant31.1 (15.7) Bilateral CI58.5% Contralateral HA (bimodal)15% Maternal education college or post graduate46.3%61.2% Public Insurance41.5%32.7% Income <$50, %40.8% Have siblings75%81.3%

Etiology of hearing loss: comparison CI and HA

Mean Cognitive and Language Scores Entire Group Blue: non-verbal cognitive IQ Pink: receptive language score Gray: expressive language score

Mean Cognitive and Language Scores (CI Group Only) p<0.0001

Language and cognitive characteristics among entire cohort CharacteristicNormal Cognition NVIQ>100 Low Avg Cognition NVIQ Low cognition NVIQ<80 Non-verbal IQ (SD)111 (9)90 (7)67 (10) Working Memory T Score52 (10)60 (12)59 (9) Working Memory score >6513%37%17% Receptive Language Score94 (13)77 (17)66 (12) % receptive score <8012.5%63%85% Ratio of Language:Cognition85 (12)85 (20)92.1 (31) % with language gap35%43%25%

Language and cognitive characteristics among children with CI CharacteristicNormal Cognition NVIQ>100 Low Avg Cognition NVIQ Low cognition NVIQ<80 Non-verbal IQ (SD)115 (9)91.1(7)66 (11) Working Memory T Score49 (10)59 (13)57 (6) Working Memory score >6510%33%0 Receptive Language Score86 (16)73 (16)58 (9) % receptive score <8027%71%100% Ratio of Language:Cognition75 (12)80 (18)75 (24) % with language gap73%57%44%

Factors associated with better language performance (higher ratios) in entire group PREDICTORSβp-value DECREASING NONVERBAL IQ*-0.61<.0001 BETTER WORKING MEMORY HEARING AIDS VS. UNILATERAL CI23.1<.0001 BILATERAL CI VS. UNILATERAL CI INCREASING SES SCORE2.38<.0001 BETTER AIDED SRT/SAT R2R NS: siblings, weekly hours of therapy, duration with implant/hearing age, age of implant, using any sign language, age of identification, age of child

Among children with cochlear implants, factors associated with better language performance PREDICTORSβp-value DECREASING NONVERBAL IQ* BETTER WORKING MEMORY BILATERAL CI BIMODAL – USE HA INCREASING SES SCORE R2R NS: siblings, receiving therapy, duration with implant, age of implant, using any sign language

Performance as a function of NVIQ Bilateral CI

Performance as a function of NVIQ Unilateral CI Bilateral CI

Adjusted mean language ratios by NVIQ categories Adjusted for working memory and SES

Conclusions Although many children are achieving average language abilities, many are still underperforming according to their cognitive potential –Downstream effect of language gaps There seemed to be a modest benefit to bilateral cochlear implantation on language outcomes (however more research warranted)

Thank You Jareen Meinzen-Derr, PhD (DBE) Daniel Choo, MD (ENT) Sandra Grether, PhD (SLP) Holly Barnard, PhD (Neuropsych) Julie Hibner, MS (SLP) Michael Scott, AuD (Audiology) Laura Smith, MPH (CRC) Meredith Tabangin, MPH Boys Town National Research Hospital (Mary Pat Moeller & Barbara Peterson) HRSA MCHB R40MC21513, March of Dimes #12-FY14-178