Pennington-Santerre-Lemmon-2012

Authors: Bruce F Pennington, Laura Santerre-Lemmon, Jennifer Rosenberg, Beatriz MacDonald, Richard Boada, Angela Friend, Daniel R Leopold, Stefan Samuelsson, Brian Byrne, Erik G Willcutt, Richard K Olson.

Article: Individual prediction of dyslexia by single versus multiple deficit models.

Publication: Journal of Abnormal Psychology (American Psychological Association). 121(1):212-224 2012 | DOI: 10.1037/a0025823

[Full Text]

Abstract

The overall goals of this study were to test single versus multiple cognitive deficit models of dyslexia (reading disability) at the level of individual cases and to determine the clinical utility of these models for prediction and diagnosis of dyslexia. To accomplish these goals, we tested five cognitive models of dyslexia–two single-deficit models, two multiple-deficit models, and one hybrid model–in two large population-based samples, one cross-sectional (Colorado Learning Disability Research Center) and one longitudinal (International longitudinal Twin Study). The cognitive deficits included in these cognitive models were in phonological awareness, language skill, and processing speed and/or naming speed. To determine whether an individual case fit one of these models, we used two methods: 1) the presence or absence of the predicted cognitive deficits, and 2) whether the individual’s level of reading skill best fit the regression equation with the relevant cognitive predictors (i.e., whether their reading skill was proportional to those cognitive predictors.) We found that roughly equal proportions of cases met both tests of model fit for the multiple deficit models (30-36%) and single deficit models (24-28%); hence, the hybrid model provided the best overall fit to the data. The remaining roughly 40% of cases in each sample lacked the deficit or deficits that corresponded with their best-fitting regression model. We discuss the clinical implications of these results for both diagnosis of school-age children and preschool prediction of children at risk for dyslexia.

Excerpts from full text:

This study had two overarching and related goals. One was theoretical: to test the fit of single vs. multiple deficit models of dyslexia at the level of individual cases. The second was to see how predictions derived from theoretical models inform clinical practice. Contrary to our own expectations, we found that the hybrid model, rather than the multiple deficit model, best fit the data in both samples. We also found that the “Any Deficit” profile,which corresponds to the hybrid model, outperformed other profiles in predicting both current and future cases of dyslexia.

 

So, our results indicate that the relation between predictors and reading skill are probabilistic not deterministic. This result is important for clinical practice because it means that a clinician should not require a child with dyslexia to fit a particular deficit profile or even to have any cognitive deficits in the constructs considered here.

 

In this paper, we have examined a disorder at the individual level about which more is known at the cognitive level of analysis than perhaps any other behaviorally-defined disorder, either in children or adults. Yet one clear clinical implication is that we cannot use any one of these cognitive profiles to rule in or rule out dyslexia, because of the heterogeneity of cognitive profiles among individuals with dyslexia and the probabilistic relation between cognitive deficits and dyslexia. For instance, one practice that is becoming popular in some public schools is to rule out dyslexia if the child does not have a PA deficit. Clearly, such a practice is not supported by the current results, as discussed earlier.

Tagged as: diagnosis, double deficit, multifactorial model, and phonemic awareness

Citation:

Pennington BF, Santerre-Lemmon L, Rosenberg J, et al. Individual prediction of dyslexia by single versus multiple deficit models. J Abnorm Psychol. 2012;121(1):212-224. doi:10.1037/a0025823

Leave a public question or comment:

If you need personal help or assistance, please use our contact forms instead.


All comments are moderated. Comments that are not relevant to the page topic or which contain identifiable personal information will not be published.


Your email address will not be published. Required fields are marked *