Project 1: Advances in classification and identification for specific learning disorders in reading (T1)

NIH RePORTER · NIH · P50 · $348,196 · view on reporter.nih.gov ↗

Abstract

Specific learning disorders (SLDs) in word-level reading and in reading comprehension are a public health concern given their prevalence and persistence. It is estimated that between 3% and 20% of children experience SLDs in word-level reading while 8% to 10% encounter SLDs in reading comprehension. Using the most conservative estimates, this indicates that, in the United States alone, over 5.5 million children and their families are potentially grappling with the challenges and negative consequences that accompany these conditions. Our aims are motivated by the critical need to develop improved models of identification and classification that are better informed by the substantial research literature on SLDs. Achieving the goal of improved models of identification and classification for SLDs in both word-level reading and in reading comprehension requires a two-pronged effort. The first is additional more basic research on issues associated with underlying theoretical models that potentially have implications for improved identification. The second is additional more applied research on the identification and classification models themselves. This two-pronged effort is reflected in the specific aims. Specific Aim 1 is to develop and evaluate a multi-factor model of SLDs in word-level reading that addresses their causes, consequences, and co- occurring conditions. To do this, we will implement a testable theoretical model of SLDs in word-level reading that differentiates causes, consequences, and correlates (including common co-occurring conditions) and that reflects the fundamentally developmental nature of SLDs. Specific Aim 2 is to develop and evaluate a model for classification and prediction for SLDs in word-level reading that better represents current knowledge and addresses the problem of unreliable identification. Here, we will continue development and testing of a Bayesian probabilistic model of classification and a risk prediction model that address the problem of unreliability by considering multiple criteria and that capitalizes on a recent advance in our understanding of the prevalence of SLDs in word-level reading by providing informed prior probabilities for the model. Specific Aim 3 is to examine and test alternative models of reading comprehension that are relevant to furthering our understanding of SLDs in reading comprehension. We will examine and test alternative models of reading comprehension for the purpose of generating competing and testable explanations of the origins of specific reading comprehension disorder. Specific Aim 4 is to expand our understanding of the nature and origins of SLDs in reading comprehension by comparing alternative frameworks of identification and prediction. To do this, we will apply a comprehensive approach to exploring the nature of specific reading comprehension deficit by testing whether the severity of children’s reading comprehension difficulties is driven by a latent decoding disorder, a l...

Key facts

NIH application ID
10925388
Project number
5P50HD052120-17
Recipient
FLORIDA STATE UNIVERSITY
Principal Investigator
RICHARD K WAGNER
Activity code
P50
Funding institute
NIH
Fiscal year
2024
Award amount
$348,196
Award type
5
Project period
2006-07-01 → 2028-07-31