Publications by authors named "Claire Selin"

Cross-sectional data allow the investigation of how genetics influence health at a single time point, but to understand how the genome impacts phenotype development, one must use repeated measures data. Ignoring the dependency inherent in repeated measures can exacerbate false positives and requires the utilization of methods other than general or generalized linear models. Many methods can accommodate longitudinal data, including the commonly used linear mixed model and generalized estimating equation, as well as the less popular fixed-effects model, cluster-robust standard error adjustment, and aggregate regression.

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Background: While researchers have found a link between childhood maltreatment and language difficulties, the underlying mechanisms remain unclear and replication across the literature is inconsistent.

Objective: To conduct a systematic review examining the methodological inconsistencies related to studies' samples construction, maltreatment measurement, and language outcomes using a language acquisition theory-based approach.

Methods: Using the PRISMA framework, a literature search was conducted across five databases to identify studies that have investigated the effects of maltreatment on the language dimensions of vocabulary and grammar.

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Background: Children exposed to adversity are at increased risk for underachievement in reading; however, how early that risk appears and the mechanisms underlying that risk are unclear.

Objective: Identify whether individual variation in nonword repetition-a clinical indicator of language and reading ability-can be captured in early childhood (three- to five-years-old) and how various features of adversity exposure (e.g.

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The present study elucidates heterogeneity in post-traumatic stress symptoms (PTSS) across adolescence in a sample of youth who have experienced myriad types and combinations of potentially traumatic events (PTEs), including substantiated physical abuse, sexual abuse, neglect and/or at least one other self-reported PTE. A machine learning technique was used to assess a multivariate set of variables (e.g.

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Purpose: Children exposed to adversity (e.g., chronic poverty, traumatic events, and maltreatment) are at increased risk for performing below age expectations on norm-referenced language assessments, but it is unknown whether the risk is higher for specific language impairment (SLI).

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Purpose: Children with specific language impairment (SLI) are underidentified, despite a robust literature on their language abilities and a clinical grammar marker. Adlof and Hogan (2019) call for school systems to assess oral language and provide supports through response to intervention (RTI), with the aim of identifying and supporting children with SLI and other language impairments. However, it is unknown how teachers make educational decisions for children with SLI.

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Article Synopsis
  • Research shows that work settings (like schools vs. healthcare) impact how clinical services for specific language impairments (SLI) are provided, affecting advocacy and eligibility for services.
  • A survey of speech-language pathologists revealed that healthcare-based practitioners have fewer eligibility restrictions and more flexible criteria than their school-based counterparts.
  • Differences in work settings contribute to the underidentification of individuals with SLI, highlighting the need for targeted advocacy tailored to the specific challenges faced in each setting.
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Purpose The speech-language pathologist's (SLP's) role for the specific language impairment (SLI) population is to provide specialized intervention targeting underlying deficits. However, children with SLI are often underrepresented on caseloads despite a high prevalence of the disorder and known long-term impacts. This study explored how SLPs use research to inform clinical decision making for SLI under neutral workplace circumstances.

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