Use a 30-minute neurophysiological assessment of consonants-in-noise coding for early identification of children at risk for language and literacy problems¶

Strategy · All strategies
Evidence · 4 claims (4 for) · 2 studies (2 associational), q3 · 2 of 2 report an effect size · 1 claim rests on one study

Description¶

The article recommends, on the strength of its predictive findings, that evaluating the neural coding of speech in noise can serve as an objective screen to identify at-risk children before reading instruction begins. As the authors put it, "Evaluating the neural coding of speech in noise may provide an objective neurophysiological marker for these at-risk children, opening a door to early and specific interventions." The assessment is a passive recording while children watch a film, requiring no behavioral compliance with paper-and-pencil tests.

Design Implications¶

Context¶

Requirements¶

• FFR recording equipment and the standardized [da]-in-babble paradigm; the regression model derived here applied without refitting

Constraints¶

• The authors state it is most effective at clearing children as unlikely to develop an LD rather than at diagnosis, and that replication in a larger sample is necessary

Target Learners¶

• preschool children too young for standardized phonological tests
• children difficult to test using conventional means

Target Learning Goals¶

• early identification of risk for reading and language learning problems

Affordances¶

• Consonants In Noise Ffr Biomarker Framework

Claims¶

• The consonants-in-noise model predicts concurrent reading in school-aged children and reliably classifies externally diagnosed learning disability, being most effective at clearing children as unlikely to have an LD [+M]
• A consonants-in-noise model derived in 4-year-olds generalizes to predict rapid naming and sentence memory in preschoolers, though not sentence memory in 3-year-olds [+M]
• Neural coding of consonants in noise strongly predicts phonological processing in 4-year-old pre-readers over and above demographic factors [+W]
• Preschool neurophysiological assessment predicts performance on phonological processing, rapid naming, sentence memory, sight word reading, spelling, and composite reading one year later [+M]

Related Strategies¶

Examples¶

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Key Sources¶

• White-Schwoch T, Woodruff Carr K, Thompson EC, Anderson S, Nicol T, Bradlow AR, et al. (2015) Auditory Processing in Noise: A Preschool Biomarker for Literacy. PLoS Biol 13(7): e1002196. https://doi.org/10.1371/journal.pbio.1002196