In the present study, we extended prior work on the cognitive profiles of LD in reading and mathematics by focusing on the intermediate grades, by considering four academic domains that include higher and lower order skills, by taking a developmental approach to consider how cognitive dimensions at the beginning of third grade support development through the end of fifth grade, and by formally conducting academic as well as cognitive multivariate profile analysis. We began by exploring the extent to which demographic patterns recur in the various forms of LD. Except for sex, which was associated only with reading comprehension LD (i.e., more males experienced reading comprehension LD), demographic patterns were largely similar across LD in the four academic areas. There was no association between ELL and LD in any academic domain; across all four academic areas, LD was associated with subsidized lunch status and racial/ethnic background; and for three academic areas (all but word reading), race/ethnicity was related to LD status, with a greater proportion of African American students experiencing the severe academic underachievement associated with LD. The patterns of subsidized lunch and race associated with LD suggest the deleterious role poverty can play in determining academic competence.
These demographic patterns aside, however, results generally provide support for the specificity hypothesis, in which the unexpected underachievement associated with LD is conceptualized in terms of distinctive patterns of cognitive and academic strengths and weaknesses. A notable exception was the cognitive profile of students with calculations LD. Based on prior work, we had hypothesized that students with calculations LD would manifest a distinctive profile characterized by specific deficits in processing speed (e.g.,
Bull & Johnston, l997;
Fuchs et al., 2005; Geary et al., 2006;
Hecht et al., 2001) and working memory (
Barrouillet et al., 1997;
Engle et al., 1999;
Geary et al., 2007;
Swanson & Beebe-Frankenberger, 2004). By contrast, results demonstrated that performance on the five cognitive dimensions was similarly flat for students with and without LD. It is possible that calculation skill from third through fifth grade, which is complicated by the introduction of rational numbers, may alter the salient cognitive underpinnings of development (see
Hecht, in press), which we failed to consider. Future work may provide greater insight by separating measures of whole number and rational number calculation skills and assessing a broader set of cognitive dimensions.
Although there was no distinctive cognitive profile associated with calculations LD, distinctive patterns of cognitive strengths and weaknesses did emerge for the other three LD areas. Moreover, a distinctive pattern of academic strengths and weaknesses was identified in all four LD areas. Readers should note that where we consider effects that only approach significance, we note this by including the p value. We chose to include effects that approach significance given the small sample sizes of the LD groups, which undermine statistical power. To avoid this limitation, future studies should include larger representative samples to yield larger sample sizes for the LD groups.
In terms of cognitive profiles, whereas NLD students manifested a flat pattern of performance across cognitive dimensions, students with reading comprehension LD were low relative to their other cognitive abilities on language, a composite variable that included listening comprehension, oral vocabulary, and syntax. This finding corroborates earlier studies demonstrating the role these oral language abilities play in reading comprehension (e.g.,
Catts et al., 2001;
Dickinson et al., 2003;
Leach et al., 2003;
McCardle et al., 2001;
Muter et al., 2004;
Nation et al., 2001;
Nation & Snowling, 1998, 1999;
Oakhill et al., 2003;
Scarborough, 2005;
Sénéchal et al., 2006). More surprisingly, in contrast to NLD students who manifested a flat pattern of performance across cognitive dimensions, students with word reading LD were low relative to other cognitive abilities on working memory and oral language (
p = .051). It is possible that multisyllabic word identification, as required on the word reading measure at the end of fifth grade, taps more sophisticated oral language abilities than does earlier word-level skills. Support for this can be found in the adult literature on multisyllabic word reading where semantic properties of words independently predict accuracy and latency of pronunciations above and beyond word length, phonological properties, and other word-level features (see
Balota, Yap, Cortese, 2006;
Yap & Balota, 2009). In addition, new evidence from behavioral and neuroimaging studies implicates working memory deficits in children and adults with developmental dyslexia (e.g.,
Beneventi, Tønnessen, Ersland, & Hugdahl, 2010;
Berninger, Raskind, Richards, Abbott, & Stock, 2008;
Smith-Spark & Fisk, 2007) that affect word reading ability (
Berninger et al., 2006). So although working memory is not frequently identified as a salient predictor of word-level reading skill in the earlier grades, it is possible that this cognitive ability relates better to multisyllabic word-level skills as reflected at the end of fifth grade. Decoding of multisyllabic words appears to require students to hold associations between letters and sounds while building subsequent associations and tying the series together into a word, and
Conners et al. (2001) demonstrated such a relation in 8- to 12-year-olds. In terms of applied problems LD profile analysis revealed low performance on concept formation relative to other cognitive dimensions (whereas the performance of NLD students was flat across cognitive dimensions), and concept formation has been associated in previous work with word-problem skills at third grade (e.g.,
Fuchs et al., 2008).
For each of these three LD categories, the distinctive cognitive strength was processing speed. We offer two competing hypotheses of how processing speed interacts with the other cognitive processes to affect academic performance. The first posits that this relative strength on processing speed mitigates the cognitive difficulties that undermine academic competence, making their deficits in the reading comprehension, word reading, or applied problems content tapped by the end of fifth grade less severe than would otherwise be. The second posits that processing speed in only weakly related to the other cognitive processes and academic skills, and therefore selection of children into the three LD categories has little effect on the normal distribution of processing speed resulting in near mean performance. The present study does not provide the means for evaluating this hypothesis. Research is needed to explore whether relative strength in processing speed affects the execution of lower-level skills that are embedded within more complex tasks and therefore reduces the deleterious effects of other cognitive deficits that undermine academic competence.
With respect to academic profiles, by definition, students with LD experience academic difficulty in the area where LD occurs. According to the specificity hypothesis, however, LD students not only should manifest deficits in the area of their LD but also should demonstrate pockets of relative academic strength. This stands in contrast to generalized academic deficiencies, of comparable magnitude across academic areas, as would be expected for students with mental retardation. In fact, our academic profile analyses supported the specificity hypothesis in all four academic LDs. Although NLD students experienced flat performance across the four academic areas, reading comprehension LD students demonstrated relative strength on calculations (p = .07), students with word reading LD experienced relative strength on applied problems and reading comprehension, students with applied problems LD manifested relative strength on reading comprehension and word reading, and students with calculations LD showed relative strengths on reading comprehension and word reading.
Results of these profile analyses not only lend support to the LD specificity hypothesis and the validity of the LD construct but also provide insight into the extent to which reading and mathematics LD overlap. Although findings were not entirely consistent, we found two sources of tentative support for the notion that LD is more specific to reading or mathematics than overlapping. First, for reading LD, the area or areas of academic relative strength tended to occur in mathematics; for mathematics LD, the area or areas of academic relative strength tended to occur in reading. The one exception to this pattern was word reading LD, for which reading comprehension (as well as applied problems) was identified as a relative strength.
The second source of support for the notion that LD is more specific than general to reading or mathematics is found in our estimates of the overlap between these conditions. On higher order skills, 2.6% of the 684 students in this study experienced both forms of LD (reading comprehension and applied problems); but the great majority of students were designated as LD in one or the other academic area: 5.8% only on reading comprehension and 5.6% only on applied problems. A similar pattern emerged for lower-order skills, even though a different test, with a different normative framework, was employed. That is, 3.8% of the 684 students in the study were identified as having word reading as well as calculations LD, whereas most students experienced LD in word reading (6.6%) or calculations (10.1%). Consequently, results indicate that although comorbidity does occur, it is limited to approximately 20% of students with LD, adding credence to the notion that reading and mathematics LD may be distinct.
That most students do not experience the severe academic deficits associated with LD across reading and mathematics is supported by
Dirks, Spyer, van Lieshout, and de Sonneville (2008), who found that when using the 25th percentile as the cut point, 7.6% of their sample was classified with comorbid reading and mathematics LD whereas 19.9% was identified as specific word reading LD and 10.3% as specific calculations LD; when using the 10th percentile, the prevalence of comorbidity was lower (1.0%), 8.0% identified as word reading LD and 5.6% as calculations LD. Our prevalence rate, which was based on a cut point of the 15th percentile, fell in the middle Dirks et al.'s estimates, as would be expected. That reading and mathematics LD may be distinct gains credence from findings that there are independent genetic sources of variation related to measures of decoding fluency and mathematics (
Hart, Petrill, & Thompson, 2010). Moreover, in randomized controlled trials, students with mathematics LD alone and those with comorbid reading and mathematics LD respond comparably to number combination or word-problem remediation (e.g.,
Fuchs et al., 2009). Even so, some work suggests that most students with reading LD appear to have active mathematics individual educational programs (
Kavale & Reese, 1992), although we could not locate more recent or national estimates.
Before closing, we note several study limitations that readers should consider when interpreting the findings. First, as already mentioned, our sample sizes for the LD groups were small. This is understandable given that LD required academic performance below the 15th percentile. Even so, the small sample sizes make it difficult to detect differences when following up the significant multivariate interactions. Second, our reading and mathematics measures involved different tests (for reading comprehension, WRMT; for word reading and calculations, WRAT; and for applied problems, WJ-III Applied Problems), each with a different normative sample. Although this did not affect the academic profile analyses, for which we relied on this study's normative sample, the use of different national norms in the various tests does affect the identification of LD, and readers should exercise caution with respect to the estimates of prevalence reported in the results section. The third limitation of the present study is that our exploration of cognitive dimensions was limited to nonverbal problem solving, processing speed, concept formation, language, and working memory. It is possible that the inclusion of other cognitive dimensions, such as phonological processing and rapid naming speed, or the use of different measures representing the cognitive dimensions we did include may result in a different pattern of results. Clearly, in light of these methodological limitations, additional research is warranted on the LD specificity hypothesis, about the nature of distinctive strengths and weaknesses of LD, and concerning whether reading and mathematics LD are distinct.
The publisher's final edited version of this article is available at 
