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Assessment for Developmental Language Disorder
Presenter(s): Suzanne Adlof, PhD
Credit(s): PDHs: 2.0, ASHA CEUs*: 0.2
Summary: This webinar will provide information to help SLPs feel more confident during the challenging process of assessing and diagnosing children with developmental language disorder (DLD). The webinar will define, compare, and contrast the features associated with various assessment tools and discuss the rationale for different assessments. The speaker will address how to select the best assessment instrument for the particular child and how to utilize information gained to inform clinical decisions. The speaker will combat common misconceptions about language assessments and provide practical, evidence-based strategies for assessment planning and interpretation. Using case studies and clinical scenarios, the presenter will demonstrate a collaborative, multidisciplinary approach that integrates data across assessments.
Presenter(s): Rebecca Witmer, LCSW; Kaitlyn Mulray, MS, CCC-SLP; Melissa Ferrello, AuD, CCC-A
Credit(s): PDHs: 1.0, ASHA CEUs*: 0.1
Summary: TMPRSS3 is a genetic variant associated with either progressive or congenital bilateral sensorineural hearing loss. Through case studies, this live webinar (June 5, 2024, 2-3 p.m. ET) will address multidisciplinary management spanning from diagnosis of hearing loss to cochlear implantation. The presenters will share relevant education for professionals working with children with hearing loss.
Credit(s): PDHs: 5.5, ASHA CEUs*: 0.55
Summary: The articles in this journal self-study discuss the literacy difficulties many children with autism spectrum disorder (ASD) experience, with direct clinical implications for literacy assessment and intervention. The articles, which apply to children across the age spectrum, are from a 2021 forum published in Language, Speech, and Hearing Services in Schools, titled “Literacy in Autism—Across the Spectrum.”
Credit(s): PDHs: 7.0, ASHA CEUs*: 0.7
Summary: SLPs are working with an increasing number of children and families who identify as bilingual, multilingual, or dual language learners (DLLs). This journal self-study explores how family expectations can impact the effectiveness of interventions, how expectations may vary across cultures, and what SLP interventions are considered evidence-based when working with DLLs and culturally and linguistically diverse families.
Credit(s): PDHs: 8.5, ASHA CEUs*: 0.85
Summary: SLPs are tasked with evaluating dual language learners (DLLs), often without speaking the language the child uses most. This journal self-study explores emerging practices that SLPs can use to improve overall assessment quality and outcomes when working with diverse DLLs.
Credit(s): PDHs: 9.0, ASHA CEUs*: 0.9
Summary: This journal self-study course is composed of papers from a 2019 Research Forum, Advancing Statistical Methods in Speech, Language, and Hearing Sciences. These selected articles provide advanced-level discussion about clinically relevant statistical methodologies to give speech-language pathologists a stronger foundation from which to analyze and understand the statistical research they come across to decide when and how to apply it in practice.
Credit(s): PDHs: 6.0, ASHA CEUs*: 0.6
Summary: This journal self-study course compares language performance in children with and without cochlear implants from preschool to 6th grade. The articles examine levels of language from phonology to prosody, offering insights into areas of strength and weakness as well as clinical directions. The first article examines consonant acquisition patterns based on hearing exposure. The second and third articles compare morphosyntactic, lexical, and phonological awareness profiles, the effect of literacy on each language skill, and types of errors produced in school-age children with and without cochlear implants. The fourth article explores differences in word-learning strategies that could affect lexical development and offers clinical suggestions based on these findings. The final article explores children’s abilities to discriminate emotional intent based on suprasegmental characteristics in the speech signal.