Examining the Etiology of Reading Disability as Conceptualized by the Hybrid Model

Revisiting the definition of dyslexia

The International Dyslexia Association definition of dyslexia was updated 20 years ago and has been referenced frequently in research and practice. In this paper, researchers from the Florida Center for Reading Research consider the components of the definition and make recommendations for revisions. These include recognizing the persistence of word-reading, decoding, and spelling difficulties, acknowledging the multifactorial causal basis of dyslexia, clarifying exclusionary factors, and denoting comorbidity with other developmental disorders. It is also suggested that the academic and psychosocial consequences of dyslexia be highlighted to reinforce a preventive service delivery model. Lastly, the inclusion of dyslexia within a specific learning disability category is supported.

The relation between reading and externalizing behavior: a correlational meta-analysis

Reading proficiency is important because it has life-long consequences and influences success in other academic areas. Many students with behavior problems are poor readers and many students with learning disabilities have more behavior problems than their typical peers. We conducted a correlational meta-analysis to examine the association between reading and externalizing behavior in students ages 5-12. We identified 33 studies that reported 88 effect sizes. Using a random-effects linear regression model with robust variance estimation, we found a significant, negative correlation (r= -0.1698, SE = 0.01, p < 0.0001) between reading and externalizing behavior. We tested several moderators related to measurement and sample characteristics. We found that rater type, behavior dimension (e.g., aggression), time between longitudinal measurement points, age of the sample, and percentage male of the sample moderated the relation between reading and behavior. Whether the reading assessment measured comprehension or word reading and socioeconomic status of the sample did not moderate the relation. Understanding the association between reading and externalizing behavior has implications for disability identification and intervention practices for children in elementary school. Future research should examine shared cognitive factors and environmental influences that explain the relation between the constructs.

Developmental dyslexia susceptibility genes DNAAF4, DCDC2, and NRSN1 are associated with brain function in fluently reading adolescents and young adults

Reading skills and developmental dyslexia, characterized by difficulties in developing reading skills, have been associated with brain anomalies within the language network. Genetic factors contribute to developmental dyslexia risk, but the mechanisms by which these genes influence reading skills remain unclear. In this preregistered study (https://osf.io/7sehx), we explored if developmental dyslexia susceptibility genes DNAAF4, DCDC2, NRSN1, and KIAA0319 are associated with brain function in fluently reading adolescents and young adults. Functional MRI and task performance data were collected during tasks involving written and spoken sentence processing, and DNA sequence variants of developmental dyslexia susceptibility genes previously associated with brain structure anomalies were genotyped. The results revealed that variation in DNAAF4, DCDC2, and NRSN1 is associated with brain activity in key language regions: the left inferior frontal gyrus, middle temporal gyrus, and intraparietal sulcus. Furthermore, NRSN1 was associated with task performance, but KIAA0319 did not yield any significant associations. Our findings suggest that individuals with a genetic predisposition to developmental dyslexia may partly employ compensatory neural and behavioral mechanisms to maintain typical task performance. Our study highlights the relevance of these developmental dyslexia susceptibility genes in language-related brain function, even in individuals without developmental dyslexia, providing valuable insights into the genetic factors influencing language processing.

Early Identification of Children with Dyslexia: Variables Differentially Predict Poor Reading Versus Unexpected Poor Reading

Definitions of dyslexia typically make reference to unexpected poor reading, although how best to operationalize unexpected remains an issue. When operationally defined as reading below expectations based on level of oral language, cases of unexpected poor reading make up fewer than half of cases of poor reading, and cases of unexpected poor reading occur throughout the range of reading proficiency. An implication is that what optimally predicts poor reading may not optimally predict unexpected poor reading. The goal of the three presented studies was to test this implication empirically. In Study 1, a model-based meta-analysis, phonological awareness accounted for 40% of the variance in decoding but only 1% of the variance in decoding that was unexpected based on level of vocabulary. Conversely, unexpected phonological awareness accounted for 34% of the variance in unexpected decoding but only 1% of the variance in decoding. An analogous pattern of results occurred for reading comprehension. In Study 2, a study of 766 children in kindergarten, first grade, and second grade, latent variables were used to represent oral vocabulary, phonological awareness, and decoding. As was seen in Study 1, unexpected decoding was better predicted by unexpected phonological awareness than by phonological awareness. In Study 3, a longitudinal study of 1,025 children followed from preschool through grade 2, the pattern of results mirrored those of Studies 1 and 2. An important implication of these studies is that typical assessments may be better at identifying poor reading than they are at identifying unexpected poor reading or dyslexia.

A Bayesian Probabilistic Framework for Identification of Individuals with Dyslexia

Purpose

Bayesian-based models for diagnosis are common in medicine but have not been incorporated into identification models for dyslexia. The purpose of the present study was to evaluate Bayesian identification models that included a broader set of predictors and that capitalized on recent developments in modeling the prevalence of dyslexia.

Method

Model-based meta-analysis was used to create a composite correlation matrix that included common predictors of dyslexia such as decoding, phonological awareness, oral language, but also included response to intervention (RTI) and family risk for dyslexia. Bayesian logistic regression models were used to predict poor reading comprehension, unexpectedly poor reading comprehension, poor decoding, and unexpectedly poor decoding, all at two levels of severity.

Results

Most predictors made independent and substantial contributions to prediction, supporting models of dyslexia that rely on multiple rather than single indicators. RTI was the strongest predictor of poor reading comprehension and unexpectedly poor reading comprehension. Phonological awareness was the strongest predictor of poor decoding and unexpectedly poor decoding, followed closely by family risk.

Conclusion

Bayesian-based models are a promising tool for implementing multiple-indicator models of identification. Ideas for improving prediction and implications for theory and practice are discussed.

Exploring the Machine Learning Paradigm in Determining Risk for Reading Disability

Purpose

Researchers have developed a constellation model of decoding-related reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation model framework. However, some issues may arise with applying the logistic regression method (e.g., multicollinearity). Machine learning techniques, such as random forest (RF), might assist in overcoming these limitations. They can better deal with complex data relations than traditional approaches. We examined the prediction performance of RF and compared it against LR to determine RD risk.

Method

The sample comprised 12,171 students from Florida whose third-grade RD risk was operationalized using the constellation model with one, two, three, or four RD indicators in first and second grade.

Results

Results revealed that LR and RF performed on par in accurately predicting RD risk. Regarding predictor importance, reading fluency was consistently the most critical predictor for RD risk.

Conclusion

Findings suggest that RF does not outperform LR in RD prediction accuracy in models with multiple linearly related predictors. Findings also highlight including reading fluency in early identification batteries for later RD determination.

Insights into Dyslexia Genetics Research from the Last Two Decades

Dyslexia, a specific reading disability, is a common (up to 10% of children) and highly heritable (~70%) neurodevelopmental disorder. Behavioral and molecular genetic approaches are aimed towards dissecting its significant genetic component. In the proposed review, we will summarize advances in twin and molecular genetic research from the past 20 years. First, we will briefly outline the clinical and educational presentation and epidemiology of dyslexia. Next, we will summarize results from twin studies, followed by molecular genetic research (e.g., genome-wide association studies (GWASs)). In particular, we will highlight converging key insights from genetic research. (1) Dyslexia is a highly polygenic neurodevelopmental disorder with a complex genetic architecture. (2) Dyslexia categories share a large proportion of genetics with continuously distributed measures of reading skills, with shared genetic risks also seen across development. (3) Dyslexia genetic risks are shared with those implicated in many other neurodevelopmental disorders (e.g., developmental language disorder and dyscalculia). Finally, we will discuss the implications and future directions. As the diversity of genetic studies continues to increase through international collaborate efforts, we will highlight the challenges in advances of genetics discoveries in this field.

The Relation Between Academic Word Use and Reading Comprehension for Students From Diverse Backgrounds

Purpose

The aims of the current project were twofold: (a) to describe the use of academic words in written language samples by fifth-grade students and (b) to examine the predictive relation between academic word use in academic writing and reading comprehension.

Method

Investigators utilized written expository responses of 1,128 students in fifth grade who differed in English proficiency and language ability. The sample included 214 students who were English learners (ELs) and 144 students with identified language learning disabilities (LLD). Group differences in the use of academic words from the Coxhead word list were examined.

Results

ELs and students with LLD used academic words less frequently than their peers and demonstrated less variety in their academic word use. There was a significant relation between students' use of academic words and reading comprehension. Academic word use accounted for 16% of the variance in reading comprehension, which was not significantly different for ELs or students with LLD. The relation was moderated by economic advantage, with the strength of the relation being lower for students who were eligible for free/reduced lunch.

Conclusions

Findings support the need for additional research on ways to improve academic vocabulary skills to minimize achievement gaps. The relation between academic word use and reading comprehension warrants further consideration.

Developmental dynamics between reading and math in elementary school

Reading and math attainment develop during elementary grades. Questions remain, though, about the co-developmental nature of the relation between reading and math. This study examined dynamic, longitudinal pathways between reading and math in first through fourth grades. Participants of the study were 554 academically at-risk children (Mage at the first assessment point = 6.57 years; SD = 0.38) from Texas Project Achieve. Children were assessed utilizing the Woodcock-Johnson-III reading and math measures. Results from dynamic bivariate latent change score models indicated unidirectional longitudinal coupling effects from reading to math. Specifically, average and high levels of reading performance were associated with subsequent gains in math growth, in particular for below average performing children in math. In contrast, low levels of reading performance had negligible or no amplifying influences on change in math growth. The nature of the dynamics was replicated even when controlling for nonverbal cognitive abilities. Results demonstrated that good reading skills pave the way for children to develop their math skills. Such findings underscore the importance of considering reading performance in treating math difficulties.

How the Science of Reading Informs 21st-Century Education

The science of reading should be informed by an evolving evidence base built upon the scientific method. Decades of basic research and randomized controlled trials of interventions and instructional routines have formed a substantial evidence base to guide best practices in reading instruction, reading intervention, and the early identification of at-risk readers. The recent resurfacing of questions about what constitutes the science of reading is leading to misinformation in the public space that may be viewed by educational stakeholders as merely differences of opinion among scientists. Our goals in this paper are to revisit the science of reading through an epistemological lens to clarify what constitutes evidence in the science of reading and to offer a critical evaluation of the evidence provided by the science of reading. To this end, we summarize those things that we believe have compelling evidence, promising evidence, or a lack of compelling evidence. We conclude with a discussion of areas of focus that we believe will advance the science of reading to meet the needs of all children in the 21st century.

The Prevalence of Dyslexia: A New Approach to Its Estimation

How prevalent is dyslexia? A definitive answer to this question has been elusive because of the continuous distribution of reading performance and predictors of dyslexia and because of the heterogeneous nature of samples of poor readers. Samples of poor readers are a mixture of individuals whose reading is consistent with or expected based on their performance in other academic areas and in language, and individuals with dyslexia whose reading is not consistent with or expected based on their other performances. In the present article, we replicate and extend a new approach for determining the prevalence of dyslexia. Using model-based meta-analysis and simulation, three main results were found. First, the prevalence of dyslexia is better represented as a distribution that varies as a function of severity as opposed to any single-point estimate. Second, samples of poor readers will contain more expected poor readers than unexpected or dyslexic readers. Third, individuals with dyslexia can be found across the reading spectrum as opposed to only at the lower tail of reading performance. These results have implications for screening and identification, and for recruiting participants for scientific studies of dyslexia.

Combining Old and New for Better Understanding and Predicting Dyslexia

Despite decades of research, it has been difficult to achieve consensus on a definition of common learning disabilities such as dyslexia. This lack of consensus represents a fundamental problem for the field. Our approach to addressing this issue is to use model-based meta-analyses and Bayesian models with informative priors to combine the results of a large number of studies for the purpose of yielding a more stable and well-supported conceptualization of reading disability. A prerequisite to implementing these models is establishing informative priors for dyslexia. We illustrate a new approach for doing so based on the known distribution of the difference between correlated variables, and use this distribution to determine the proportion of poor readers whose poor reading is unexpected (i.e., likely to be due to dyslexia) as opposed to expected.

Differential Identification of Females and Males with Reading Difficulties: A Meta-Analysis

Males are more likely than females to be identified as having reading difficulties, but it is unclear if this is a result of sample ascertainment or identification bias. The purpose of this meta-analysis was to determine the magnitude of gender differences in reading difficulties using available studies in which researchers investigated this difference and an additional dataset with a representative U.S.

SAMPLE

After conducting a literature search, sixteen studies and a restricted use dataset were included in the present analysis (N = 552,729). A random-effects odds ratio (OR) model indicated that males are 1.83 times more likely than females to have reading difficulties. Moderator analyses revealed that the gender ratio is greater when the identified reading difficulties were more severe. Further, this difference in identification rates across males and females was found without evidence of publication bias. Implications for the identification of students with reading difficulties are discussed.