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Record W3036630428 · doi:10.1542/peds.2019-3046

Reintroducing Dyslexia: Early Identification and Implications for Pediatric Practice

2020· review· en· W3036630428 on OpenAlexaff
Joseph S. Sanfilippo, Molly Ness, Yaacov Petscher, Leonard Rappaport, Barry Zuckerman, Nadine Gaab

Bibliographic record

VenuePEDIATRICS · 2020
Typereview
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsQueen's University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsDyslexiaMedicineAnxietyPsychological interventionDevelopmental psychologyIdentification (biology)NeuroimagingLiteracyReading (process)Clinical psychologyCognitionSocioeconomic statusAttention deficit hyperactivity disorderLearning disabilityBiological theories of dyslexiaPsychiatryCognitive psychologyPsychologyPopulationDevelopmental dyslexia

Abstract

fetched live from OpenAlex

Dyslexia is a common learning disorder that renders children susceptible to poor health outcomes and many elements of socioeconomic difficulty. It is commonly undiagnosed until a child has repeatedly failed to learn to read in elementary school; this late diagnosis not only places the child at an academic disadvantage but also can be a precursor to psychiatric comorbidities such as anxiety and depression. Genetic and neuroimaging research have revealed that dyslexia is heritable and that it is undergirded by brain differences that are present even before reading instruction begins. Cognitive-behavioral research has revealed that there are early literacy skill deficits that represent red flags for dyslexia risk and can be measured at a preschool age. Altogether, this evidence points to dyslexia as a disorder that can be flagged by a pediatrician before school entry, during a period of heightened brain plasticity when interventions are more likely to be effective. In this review, we discuss the clinical implications of the most recent advances in dyslexia research, which converge to indicate that early identification and screening are crucial to the prevention or mitigation of adverse secondary consequences of dyslexia. We further highlight evidence-based and practical strategies for the implementation of early risk identification in pediatric practice so that physicians can be empowered in their ability to treat, educate, and advocate for their patients and families with dyslexia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.401
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations113
Published2020
Admission routes1
Has abstractyes

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