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Moderating Effects of Spoken Language in the Home on the Relations Between Age at Diagnosis and ASD Symptoms and Expressive Language for Young Children with ASD Screened in Early Intervention

Friday, May 15, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
F. Martinez-Pedraza, M. Maye and A. S. Carter, Department of Psychology, University of Massachusetts Boston, Boston, MA
Background:  Racial/ethnic minority children are less likely to receive an early ASD diagnosis (Mandell et al., 2009; Valicenti-McDermott et al., 2012), and more likely to show more severe ASD symptoms and language delays once diagnosed (Liptak et. al, 2008; Tek & Landa, 2012). Lower ASD prevalence rates among racial/ethnic minorities have been examined as a function of parental nativity, SES, education and spoken language (Fountain & Bearman, 2011; Kogan et al., 2009; Thomas et al., 2012). However, little is known about whether symptom presentation and/or other sociodemographic factors (e.g., spoken language) predict age at diagnosis in the context of early screening.

Objectives:  To examine main effects and interactions of language spoken in the home with children’s ASD symptoms and expressive language on children’s age at evaluation.

Methods: Forty-six toddlers (ages 16-33 months) screened for ASD by Early Intervention (EI) providers were referred to our project for a diagnostic assessment due to failing an ASD observational screener and/or EI provider/parental ASD concern. In this socioeconomically-diverse sample (51% with yearly incomes <$35,000), 78% were racial/ethnic minorities and 22% were non-minorities; 65% only spoke English at home, and 35% were English Language Learners (ELL). Children were assessed with the ADOS-2 and the Mullen Scales. Additional participants (~50) will be added to the dataset at time of presentation.

Results: There was a significant interaction between spoken language in the home and ASD symptoms predicting to age at evaluation (β = -.430, t(4) = -3.090, p < .05, ηp2 = .230). ASD symptoms did not contribute to age at evaluation for referred children whose only language exposure was English (r(21) = .024, p > .05). However, ASD symptoms was a significant predictor of age at evaluation for ELL children screened and referred to a diagnostic evaluation (r(9) = -.853, p = .001). ELL children with more ASD symptoms were referred for an evaluation at younger ages than ELL children with fewer ASD symptoms. Expressive language also predicted age at evaluation (β = -.482, t (4) = -3.397, p < .05, ηp2 = .265), explaining 19% of the variance in the model. For all children, higher expressive language scores predicted an earlier age at evaluation. The final model included ASD symptoms, spoken language in the home, expressive language, and the interaction between symptoms and spoken language, and explained 48% of the total variance in age at evaluation.

Conclusions: These findings indicate differences in how ASD symptoms predict age at diagnostic evaluations based on children’s ELL status. Biases in the early screening and identification of ELL children may be impacting EI providers’ referrals for further diagnostic evaluation. Perhaps, delays in the referral process relate to EI providers’ hesitance in referring ELL children due to uncertainty about how children’s multiple languages affects their social development, or to their communication challenges when discussing child behavior concerns with ELL families. Regardless, addressing differences in early referrals for diagnostic evaluations between ELL children and children with English-only language exposure is critical to reduce the identification gap among linguistically-diverse children.