Reading Comprehension and Reading Related Abilities in Adolescents with Reading Disabilities and Attention- Deficit/Hyperactivity Disorder

Transcription

1 & Reading Comprehension and Reading Related Abilities in Adolescents with Reading Disabilities and Attention- Deficit/Hyperactivity Disorder Karen Ghelani 1,2, Robindra Sidhu 1, Umesh Jain 3 and Rosemary Tannock 2, * 1 Ontario Institute for Studies in Education, The University of Toronto, Toronto, Canada 2 Brain and Behavior Research Program, Research Institute, The Hospital for Sick Children, Toronto, Canada 3 The Centre for Addiction and Mental Health, Toronto, Canada Reading comprehension is a very complex task that requires different cognitive processes and reading abilities over the life span. There are fewer studies of reading comprehension relative to investigations of word reading abilities. Reading comprehension difficulties, however, have been identified in two common and frequently overlapping childhood disorders: reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD). The nature of reading comprehension difficulties in these groups remains unclear. The performance of four groups of adolescents (RD, ADHD, comorbid ADHD and RD, and normal controls) was compared on reading comprehension tasks as well as on reading rate and accuracy tasks. Adolescents with RD showed difficulties across most reading tasks, although their comprehension scores were average. Adolescents with ADHD exhibited adequate single word reading abilities. Subtle difficulties were observed, however, on measures of text reading rate and accuracy as well as on silent reading comprehension, but scores remained in the average range. The comorbid group demonstrated similar difficulties to the RD group on word reading accuracy and on reading rate but experienced problems on only silent reading comprehension. Implications for reading interventions are outlined, as well as the *Correspondence to: R. Tannock, Brain and Behavior Research Program, The Hospital for Sick Children, 555 University Ave., Toronto, Ontario, Canada M5G 1X8. rosemary.tannock@sickkids.ca Published online in Wiley InterScience ( DOI: /dys.285

2 Reading Disability in Adolescents 365 clinical relevance for diagnosis. Copyright # 2004 John Wiley & Sons, Ltd. Keywords: reading disability; attention deficit hyperactivity disorder; adolescence; reading comprehension INTRODUCTION Reading comprehension is multifaceted and requires the synchrony of a number of reading related processes in order to derive meaning from text. Research on reading development has focused overwhelmingly on the acquisition of basic decoding skills while the development of comprehension has been relatively neglected. As a result, there is little research to explain why the harmonious relationship between decoding and reading comprehension sometimes becomes dissonant. Reading comprehension difficulties have been documented in two very common childhood disorders: reading disability (RD) and attention-deficit/ hyperactivity disorder (ADHD). Reading disability (RD) is a language-based disorder characterized by the failure to acquire rapid, context-free, word identification skills (Stanovich & Siegel, 1994) while ADHD is a developmental disorder comprised of difficulties with inattention, impulsivity, and hyperactivity (Barkley, 1997; DSM-IV-TR, APA, 2000). Both of these disorders are pervasive across the life span (Barkley, 1997; Shaywitz & Shaywitz, 2003). Reading Disability and ADHD co-occur more frequently than expected by chance (Fawcett & Nicolson, 2001; Fletcher, Shaywitz, & Shaywitz, 1999; Willcutt, Pennington, & DeFries, 2000) which makes the investigation of unique and shared reading abilities challenging. Reading Disability is a very heterogeneous disorder which may or may not be accompanied by reading comprehension failure (Cain, Oakhill, & Bryant, 2000; Ransby & Swanson, 2003; Simmons & Singleton, 2000; Snowling, 2001). When comprehension difficulties occur, they are usually traced to a bottleneck at the word level which leaves few attentional processes available for interpreting text (LaBerge & Samuels, 1974; Perfetti, 1985). Few studies have examined reading comprehension difficulties in individuals with ADHD. Results of one study indicated that the performance of children with ADHD, without comorbid language impairments, declined as the length of the passage increased (Cherkes-Julkowski et al., 1995). Results from another study revealed that, in spite of generally average word reading accuracy and word reading rate, children with ADHD were more impaired in the reporting of main ideas from expository passages than normal controls (Brock & Knapp, 1996). Group differences were attributed to greater demands for effortful processing on longer passages and, therefore, greater demands on attentional capacity. Reading disabilities and medication effects in the ADHD group, however, were not adequately controlled for in these two studies. Therefore, although the literature suggests reading comprehension failure in individuals with ADHD, the results remain equivocal. The literature on reading processes proposes several critical predictors of reading comprehension performance. The most robust predictor is that of

3 366 K. Ghelani et al. phonological processing. Individuals with reading disabilities have a deficit at the phonological module level which impedes their ability to discern and manipulate the distinctive sound elements that constitute language (Shaywitz & Shaywitz, 2003). Because of the nature of the phonological core-deficit (Stanovich, 2000), other abilities necessary for adequate comprehension (i.e. cognitive and linguistic functions) may remain intact (Shaywitz & Shaywitz, 2003). Another component thought to be important for reading comprehension abilities is reading fluency. Wolf and Katzir-Cohen (2001) have suggested a definition of reading fluency that incorporates reading comprehension ability:... reading fluency refers to a level of accuracy and rate where decoding is relatively effortless; where oral reading is smooth and accurate with correct prosody; and where attention can be allocated to comprehension (p. 219). Evidence for slower and more laborious word reading has been reported in individuals with RD (e.g. Young & Bowers, 1995) but not in individuals with ADHD (Brock & Knapp, 1996). Reading rate has typically been measured by tasks requiring the rapid naming of visual stimuli such as letters, digits, colors, and objects (Denckla & Rudel, 1974). Individuals with RD generally have slower naming speed across tasks with particular difficulties naming letters and digits (e.g. Wolf, 1999). For individuals with ADHD, there is growing evidence to support specific naming deficits for objects (e.g. Carte, Nigg, & Hinshaw, 1996) and colors (e.g. Tannock, Martinussen, & Frijters, 2000). It has been reported that letter- and digit-naming speed best predict the speed of reading passages in text (Young & Bowers, 1995) while the semantic properties inherent in object-naming are a better predictor of reading comprehension (Wolf & Obreg!on, 1992). Previous investigations of reading comprehension have generally focused on a younger age group, neglecting other age groups, such as adolescents. Different reading skills, however, are required of adolescents than children. For example, adolescents are required to read a variety of text genres (e.g. expository and narrative) that are increasingly complex and lengthy. Also, adolescents generally read silently and yet many standardized assessments of reading comprehension require the adolescent to read aloud (i.e. Gray Oral Reading Test). Accordingly, there were two primary objectives of this study. The primary objective was to examine reading comprehension in adolescents with a reading disability and/or ADHD using both oral and silent reading passages. The second objective was to investigate the characteristics of reading component skills in these disorders. It was predicted that both the RD group and the ADHD group would show more difficulties on reading comprehension tests relative to the normal controls. It was further predicted that the RD group would be more impaired on reading component tasks than either the normal controls or the ADHD group. It was not expected that the ADHD group would differ from normal controls on reading component skills. It was predicted that the RD group would show slower naming speed across rapid naming tasks and the ADHD group would show specific difficulties with naming objects and colors relative to the normal controls. Four groups were used (RD, ADHD, ADHD+RD, and normal controls (NC)) to better understand the specific deficits associated with each clinical group. The inclusion of a comorbid group (ADHD+RD) allowed us to determine whether these adolescents shared the deficits associated with either RD or ADHD (or

4 Reading Disability in Adolescents 367 both) or whether they exhibited a unique profile. Evidence of the latter situation would suggest that ADHD+RD is a distinct clinical condition that needs to be differentiated from both ADHD and RD. METHOD Participants A total of 96 adolescents (aged years) participated in this study: 32 ADHD (26 males and 6 females), 20 RD (10 males and 10 females), 19 ADHD+RD (15 males and 4 females), and 25 Normal Controls (NC) (15 males and 10 females). The clinical groups were recruited from several sources including referrals from mental health facilities, community referrals, and advertisements in the Learning Disability Association of Ontario (LDAO) newsletter. The normal comparison group was recruited through a newsletter advertisement in a large metropolitan hospital (Hospital for Sick Children) looking for adolescents without reading or attentional disorders to volunteer for a research study. Many of the adolescents in the normal control group were children of hospital staff (i.e. nurses, research technologists, social workers) and many of these adolescents brought along a same-aged peer. Adolescents in the three clinical groups were interviewed using the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL) which generates a DSM-IV diagnosis (Kaufman et al., 1997). The K-SADS-PL has been used extensively to make diagnostic decisions based on DSM criteria and has been validated with children aged Separate interviews were conducted with parents and adolescents by a PhD level clinical psychologist or a supervised PhD Candidate in clinical psychology (KG). When the information provided by parent and adolescent was inconsistent, the parent information superceded the adolescent report for the presence of externalizing symptoms. A Screening Interview, in addition to the Behavioral Disorders supplement, was used with participants in the normal control group, unless concerns were raised by the parent, in which case, the entire interview was used. This situation occurred for two adolescents in the control group. Parents and teachers were also required to complete the Conners Parent Rating Scale- Revised: Long Form (Conners, 1997) and the Conners Teacher Rating Scale- Revised: Long Form (Conners, 1997), respectively. To be eligible for the study, participants were required to have an estimated Full Scale IQ (FSIQ) between 80 and 130 (as determined by a composite of the Vocabulary and Matrix Reasoning subtest on the Wechsler Abbreviated Scale of Intelligence), English as their first language, and no evidence of neurological dysfunction, uncorrected sensory impairments, or a history or current presentation of psychosis. Maternal education was used as a proxy measure of SES and was obtained from the family and developmental history questionnaires (revised Ontario Health Child Study) (Boyle et al., 1993) completed by parents. These data are reported as the proportion (in percentages) of mothers from each group who had at least completed high school. The percentages of mothers obtaining at least high school education were 94 and 85% for the ADHD group and the RD group, respectively. All mothers in the normal control and comorbid ADHD+RD group reported at least high school education.

5 368 K. Ghelani et al. The majority of the adolescents in the study were in either Grade 10 or 11 and attending an urban secondary school. Most of the adolescents in the clinical groups were receiving, at least, part-time resource withdrawal for language arts and mathematics. Inclusion for the ADHD Group: The ADHD group had a confirmed diagnosis based on the following algorithm: The adolescent (1) met current diagnosis based on the summary of DSM-IV symptoms on the K-SADS-PL (Kaufman et al., 1997); (2) met clinical criteria on both the Conners Parent and Teacher questionnaires in order to establish pervasiveness of clinical problems across settings; (3) had a developmental history establishing the onset of symptoms prior to age 7; and (4) had reading scores above the 25th percentile (Standard Score 90) on both the Word Identification and the Word Attack subtests of the Woodcock Reading Mastery Test-Revised-Normative Update (WRMT-R/NU) (Woodcock, 1998). Previous school report cards, clinical reports and/or psychoeducational assessments were requested to verify the childhood diagnosis of Inattentive and Hyperactive/Impulsive subtypes. Psychiatric consultation and differential diagnosis was provided for all ADHD adolescents by a child and adolescent psychiatrist who confirmed past and current diagnosis. Further psychiatric follow-up was offered to those who required reassessment of medication or to those who would benefit from further counselling around ADHD symptoms. Inclusion for the RD Group: A reading disability diagnosis was defined by a standard score below the 25th percentile (SS 90) on one of the following subtests: Word Identification or Word Attack subtests of the Woodcock Reading Mastery Test-Revised (WRMT-R/NU) (Woodcock, 1998). A cut off of SS 90 has been used previously in the research literature (Bruck, 1992; Fletcher et al., 1998; Frankenberger & Fronzaglio, 1991; Siegel & Heaven, 1986). It should be noted that this criterion is not as rigorous as that currently used to make a diagnosis of Learning Disability within the school system. A discrepancy between IQ and achievement was not required as the literature has generally found that there are no qualitative differences in component reading skills between discrepancybased-and low-achievement-based RD children (Fletcher et al., 1994). Adolescents in the RD group did not meet criteria for a diagnosis of ADHD based on the K-SADS-PL. Individuals in the RD group had a formal diagnosis of childhood Reading Disorder or a history of severe reading difficulties. Inclusion for the ADHD+RD Group: Participants with a comorbid condition were required to meet diagnostic criteria for both ADHD and RD. Inclusion for the Normal Control Group: The normal controls (NC) were screened for RD and ADHD using the Word ID and the Word Attack subtests from the WRMT-R/NU, the Interview Screener and Behavioral Disorder Supplement on the K-SADS-PL, and the Conners Parent and Teacher Rating Scales. Adolescents with scores below the 25th percentile on the reading subtests of the WRMT-R/NU or with T-Scores above 60 on either the Parent or Teacher Conners Rating Scales were not included in the control group for this study. Group differences on standardized and diagnostic measures Table 1 presents demographic variables, as well as variables used for diagnostic purposes. The four groups of adolescents did not differ on age or in terms of the relative proportion of females (w 2 ð3, N ¼ 96Þ ¼7:00, p ¼ 0:07). A multivariate

6 Reading Disability in Adolescents 369 Table 1. Diagnostic characteristics of the ADHD, RD, ADHD+RD and control groups ADHD RD ADHD + RD Controls (1) (2) (3) (4) M SD n M SD n M SD n M SD n df F Z 2 sig. Post-hoc a Age , n.s. WASI Scores Vocabulary scaled , , 4 > 2, 3 Score Matrix reasoning , n.s. Scaled score Estimated FSIQ , > 1 > 2, 3 WRMT-R/NU Multivar. effect 6, (Word ID, attack) Word ID , , 4 > 2, 3 Standard score Word attack Standard score , , 4 > 2, 3 ADHD Subtypes (% of clinical sample) Inattentive subtype 67.4% N/A 68.4% N/A Hyperactive/ 3.6% N/A 0.0% N/A Impulsive subtype Combined subtype 29.0% N/A 31.6% N/A Conners Rating Scales Parent inattention T-Score , , 3 > 2 > 4 Parent hyperactive/ , , 3 > 2, 4 Impulsive T-score Teacher inattention , , 2, 3 > 4 T-score Teacher hyperactive/ , , 3 > 4 Impulsive T-score Note: **p50.01, p ADHD¼attention deficit hyperactivity disorder, RD¼reading disabled, ADHDþRD¼attention deficit hyperactivity disorder and reading disabled, multivar.¼multivariate, T-Scores: T ¼ mildly atypical; T ¼ moderately atypical; T ¼> 70 markedly atypical. a Tukey HSD.

7 370 K. Ghelani et al. analysis of variance (MANOVA) revealed a main Group effect for the T-Scores on the Inattentive and Hyperactive/Impulsive Indices of the Conners Parent and Teacher Rating Scales. Tukey Honestly Significant Difference (HSD) post hoc contrasts indicated that the adolescents in the three clinical groups were rated by parents and teachers as being significantly more inattentive than their peers in the normal control group. Only the adolescents in the ADHD group and the comorbid group were seen by parents and teachers as having more hyperactive and impulsive symptoms. The participants completed a number of standardized measures of intellectual, academic, and language functioning. The short form of the WASI (Wechsler Abbreviated Scale of Intelligence, Wechsler, 1999) (i.e. Vocabulary and Matrix Reasoning) was used to provide an estimate of intellectual ability. With respect to cognitive functioning, there was a main Group effect for Vocabulary but not for Matrix Reasoning. Post hoc analyses revealed that the RD groups (RD only and ADHD+RD) had significantly lower scores on the WASI Vocabulary subtest than the normal control group. All adolescents in the clinical groups had significantly lower scores on estimated FSIQ when compared to adolescents in the normal control group. By design, the RD groups (RD only and ADHD+RD) were significantly more impaired on measures of isolated word reading and decoding than either the ADHD only group or the normal control group. The ADHD group did not differ from the normal controls on word reading and decoding. Dependent Measures Reading comprehension and reading components were measured using the following tasks: (1) Reading comprehension: Both oral and silent reading comprehension abilities were measured. The measures included the Comprehension subtest of the Gray Oral Reading Tests-Fourth Edition (GORT-4) (Wiederholt & Bryant, 2001) and the Gray Silent Reading Tests (GSRT) (Wiederholt & Blalock, 2000). On the Comprehension subtest, the adolescent is asked to read passages orally. After each passage, the adolescent is requested to turn over the page to the comprehension questions that are read by the examiner. The adolescent then orally answers the five multiple-choice questions. The reader is not allowed to reread the story when answering the five multiple-choice questions. The Comprehension score is a measure of the accuracy of the adolescent s responses to questions about the content of each story that had been read. The GSRT yields a Silent Reading Quotient (SRQ) which is an indication of the adolescent s overall silent reading comprehension; however it does not provide a measure of reading rate or accuracy. The GSRT is a self-paced task in which the adolescent reads the story and is allowed to refer back to the passage to answer the five multiplechoice questions on a response sheet. The GORT-4 and the GSRT have a similar content and format as both contain short narrative passages and five multiplechoice questions. (2) Text reading rate and accuracy: The Rate and Accuracy subtests from the Gray Oral Reading Tests (GORT-4) were used. Rate measures the amount of time taken by the adolescent to read a story aloud. Accuracy measures the adolescent s ability to pronounce each word in the story correctly.

8 Reading Disability in Adolescents 371 (3) Rapid word reading: Rapid word reading efficiency was measured by subtests on the Test of Word Reading Efficiency (TOWRE) (Wagner, Torgesen, & Rashotte, 1999a). Sight Word Efficiency (SWE) assesses the number of real words that can be accurately read orally and Phonemic Decoding Efficiency (PDE) measures the number of pseudowords (i.e. nonwords) that can be accurately decoded orally. Both tests require the individual to read lists (columns) of words from top to bottom as quickly and accurately as possible for 45 seconds. (4) Rapid naming speed: The Letters, Digits, Colors, and Objects subtests from the Comprehensive Test of Phonological Processing (CTOPP) (Wagner, Torgesen, & Rashotte, 1999b) were administered. Each subtest requires the individual to name the stimuli as quickly as they can. The individual s score is the total number of seconds taken to name all of the items on two stimulus pages. Each subtest has a total of 72 items (36 items per stimulus page). Each stimulus page has four rows and nine columns of six randomly arranged items measured by the subtest (i.e. letters, digits, colors, objects). The composites of these subtests were used in the analyses. The Rapid Naming Composite Score (RNCS) is a measure of naming speed for letters and digits while the Alternate Rapid Naming Composite Score (ARNCS) is a measure of naming speed for colors and objects. Letters and digits were chosen as they have proven to be better predictors of reading performance in the RD population (Denckla & Rudel, 1974). Colors and objects were chosen as they have been shown to be more difficult for the ADHD group (Semrud-Clikeman et al., 2000; Tannock, Martinussen, & Frijters, 2000). In addition, a relationship has been found between object naming speed and reading comprehension (Wolf & Goodglass, 1986; Wolf & Obreg!on, 1992). Measures and Procedures The testing was completed in one day at the Hospital for Sick Children. Informed written consents and assents were obtained from parents and from adolescents who were 14 or 15 years of age. Adolescents aged 16 years and over provided written consents. All adolescents were asked to be off psychostimulant medication for at least 24 hours prior to testing. This required 25 of the 32 adolescents in the ADHD group and 6 of the 19 adolescents in the comorbid group who were on stimulant medication to be off medication for the day of testing. Only one adolescent with ADHD who was receiving a non-stimulant medication (Amitriptoline, an antidepressant medication) was assessed while on medication. The testing was administered by the first author (K. G.) and by two other PhD level psychology students who were trained in administering the standardized tasks. Adolescents were reimbursed $20 for their participation. All clinical participants received verbal feedback as well as a written clinical assessment of their results. A consulting psychiatrist (U. J.) was involved in the verbal feedback sessions with the ADHD participants to confirm and interpret any clinical diagnoses. Statistical Analyses: Prior to conducting statistical analyses, the data was examined for outliers. Tabachnick and Fidell s (2001, p. 71) most conservative score changing option was selected for only those tasks on which these individuals deviated extremely. This option calls for assigning the outlying case a raw score on the offending variable that is one unit larger (or smaller) than the next most extreme score in the distribution. This procedure was applied on

9 372 K. Ghelani et al. the standard scores for the rapid composite naming measures with scores being adjusted downwards: RNCS (n ¼ 1, ADHD; n ¼ 1, RD) and ARNCS (n ¼ 1, ADHD). Univariate analyses of variance (ANOVA) were used to examine group differences on measures. If the omnibus F test was significant ðp ¼ :05Þ, Tukey HSD tests were performed to determine which groups were significantly different from each other. Eta square (Z 2 ) effect sizes were computed. Eta square ranges in value from 0 1. A higher value reflects a stronger effect size (Green, Salkind, & Akey, 2000, p. 151). Covariates: The finding that the clinical groups differed from the normal control group on estimated FSIQ and vocabulary poses a methodological quandary. Some researchers (e.g. Werry, Elkind, & Reeves, 1987) argue that IQ should be included as a covariate to ensure that deficits cannot be attributed more parsimoniously to group differences in intellectual functioning (Willcutt et al., 2001). Others (e.g. Mariani & Barkley, 1997) argue that the presence of ADHD may give rise to lower scores on tests of intelligence and controlling for IQ removes the portion of the variance associated specifically with ADHD. A recent study by Kuntsi et al. (2004) documented a genetic basis for lower intelligence scores (9 points lower, on average, than comparison group) in the ADHD population. A similar argument has been presented for the reading disabled population when covarying IQ estimates that contains a vocabulary measure (Stanovich & Siegel, 1994). Since this issue remains unresolved, results for reading component and naming speed tasks have been reported with and without controlling for group differences on estimated FSIQ and Vocabulary. RESULTS Dependent Variables Table 2 reports the means, standard deviations, and F values on all of the reading measures: (1) Performance on oral and silent reading comprehension: there was a main effect for Group on both oral and silent reading comprehension tasks (GORT-4 Comprehension subtest and the GSRT). Post hoc analyses for these measures suggested that only the adolescents in the RD group had more difficulty in their ability to answer questions correctly on the oral reading comprehension measure compared to the normal group. On the silent reading passages, all clinical groups had scores that were significantly lower than the normal control group. The means for the clinical groups remained in the average range on these tasks and the scores for the RD groups (RD only and ADHD+RD) were the lowest. (2) Performance on text reading rate and accuracy: there was a main Group effect for text reading rate and accuracy measures. Post hoc analyses indicated that the clinical groups had significantly lower scores on text reading rate and accuracy as compared to the normal control group. Only the mean scores for the RD groups (RD only and ADHD+RD), however, were within the more severe range. Post hoc comparisons revealed significantly lower scores on text reading rate and accuracy for the RD groups (RD only and ADHD+RD) relative to the ADHD group.

10 Reading Disability in Adolescents 373 Table 2. Reading abilities of the ADHD, RD, ADHD+RD and control groups ADHD RD ADHD + RD Controls (1) (2) (3) (4) M SD n M SD n M SD n M SD n df F Z 2 sig Post-hoc a Reading comprehension GSRT SRQ , > 1, 3; Standard score 4 > 2; 1 > 2 GORT-4 comprehension , ** 4>2 Scaled score Text reading rate and accuracy GORT rate , Scaled score GORT-4 accuracy , Scaled score 4>1>2,3 4>1>2,3 Rapid word reading Multivar. effect 6, (SWE, PDE) TOWRE SWE , Standard score TOWRE PDE , Standard score TOWRE composite , Standard Score 4>1>2,3 4>1>2,3 4>1>2,3 Rapid naming speed Multivar. effect 6, (RNCS, ARNCS) CTOPP RNCS comp , Standard score CTOPP ARNCS comp , Standard score 1, 4 > 2, 3 4>1>3; 4>2 Note: **p50.01, p multivar.¼multivariate; comp.¼composite, GSRT¼gray silent reading tests; SRQ¼silent reading quotient; GORT-4¼gray oral reading tests, TOWRE=test of word reading efficiency; SWE¼sight word efficiency; PDE¼phonemic decoding efficiency; CTOPP¼comprehensive test of phonological processing; RNCS¼rapid naming composite score (letters, digits); ARNCS¼alternate rapid naming composite score (colors, objects).

11 374 K. Ghelani et al. In order to assess the impact of word reading on text reading rate, a one-way analysis of covariance (ANCOVA) was conducted using Word Identification and GORT-4 Accuracy as separate covariates. A preliminary analysis evaluating the homogeneity-of-slopes assumption indicated that the relationship between the covariates and reading rate did not differ significantly as a function of group. The main effect of Group and group comparisons remained significant which suggests that group differences on text reading rate are not explained by group differences on Word Identification and GORT-Accuracy. (3) Performance on rapid word reading efficiency: main group effects were obtained on the rapid word reading efficiency tasks. Post hoc analyses indicated that the clinical groups were significantly slower on both sight word and nonword reading efficiency tasks compared to the normal control group. However, as on the text reading rate and accuracy measures, the scores for the ADHD group remained within the average range. The analyses were rerun separately covarying for Word Identification and for GORT-4 Accuracy to assess the impact of single word reading on rapid word reading efficiency. The main effect of Group and group comparisons remained significant for rapid sight word reading efficiency (SWE) after controlling for these two variables suggesting that group differences on rapid word reading efficiency are not entirely explained by differences on isolated word reading or by reading accuracy. Comparable results were obtained for rapid nonword reading efficiency (PDE). The main effect of Group remained significant after covarying Word Identification. Pairwise comparisons, however, revealed that the scores for the ADHD group were only marginally significant on rapid nonword reading efficiency ðp ¼ 0:068Þ when covarying for isolated word reading and nonsignificant when covarying for text reading accuracy. (4) Performance on rapid naming speed: a main Group effect was found for rapid naming across both the RNCS (i.e. letters and digits) and the ARNCS (colors and objects) composites. Post hoc analyses showed that the RD groups (RD only and ADHD+RD) were significantly impaired on both naming composites compared to the normal group ðp ¼ :001Þ. The ADHD group, on the other hand, displayed significantly lower scores relative to the normal control group ðp ¼ 0:05Þ when naming colors and objects (but not when naming letters and digits). Paired sample t-tests were performed to compare the magnitude of the difference between the two Composite scores for the RD group and the ADHD group. The results indicated that the difference between the Composite scores was significant for the ADHD group, tð30þ ¼ 4:975, p ¼ 0:000, and marginally significant for the RD group, tð19þ ¼ 2:087, p ¼ 0:052. A one-way analysis of covariance (ANCOVA) was performed with ARNCS as the dependent variable and RNCS as the covariate. All group differences were eliminated with this analysis. When groups were compared on the basis of the number of errors made, the RD groups (RD only and ADHD+RD) made significantly more errors on digits and letters. There were no differences between the groups on color and object naming errors. Analyses controlling for estimated FSIQ and Vocabulary: the ANOVAs and MANOVAs were rerun as ANCOVAs using Bonferroni adjustment for multiple comparisons (Fleiss, 1999) to test whether the results on the dependent measures would be different when adjusting for estimated FSIQ and Vocabulary.

12 Reading Disability in Adolescents 375 The original pattern of results remained the same for reading rate for text, rapid sight word reading efficiency, and the letters and digits composite when covarying for estimated FSIQ. There were differences in results, however, on other variables. Only significant differences remained between the RD groups (RD only and ADHD+RD) and the normal controls on measures of silent reading comprehension ðfð3,89þ ¼4:197, p ¼ 0:008, Z 2 ¼ 0:12Þ, accuracy ðfð3,91þ ¼25:20, p ¼ 0:000, Z 2 ¼ 0:45Þ, and rapid nonword reading efficiency ðfð3,91þ ¼34:76, p ¼ 0:000, Z 2 ¼ 0:53Þ with the group differences between the ADHD group and the normal controls being eliminated. When controlling for the effects of Vocabulary, the pattern of group differences was similar to the results when controlling for estimated FSIQ, with two exceptions. On silent reading comprehension only the scores for the RD only group remained significantly lower than those of the normal controls. Significant differences remained between the ADHD group and normal controls on nonword reading efficiency ðfð3,91þ ¼33:55, p ¼ 0:000, Z 2 ¼ 0:53Þ when covarying Vocabulary. DISCUSSION The objectives of the present study were to examine reading comprehension abilities and reading component processes in adolescents with RD, ADHD, and comorbid ADHD+RD. As predicted, the results showed that the RD only group had lower scores on both oral and silent reading comprehension measures compared to the normal controls and the ADHD group. However, these scores were within the average range. These results are consistent with other studies that have found differences between individuals with reading disabilities and controls on reading comprehension tasks (e.g. Simmons & Singleton, 2000). The ADHD group had lower scores on silent reading comprehension relative to the normal controls but their scores were also within the average range. Our findings for the ADHD group are similar to those of a recent study (e.g. Willcutt et al., in press) that reports lower scores for the ADHD group (albeit still within the average range) than for a normal control group on silent reading comprehension. As expected, the comorbid group performed similarly to the RD group on the silent reading comprehension task, although demonstrating slightly higher scores than the RD group on the oral reading comprehension. The lower scores for the RD groups (RD only and ADHD+RD) on these comprehension measures, relative to the ADHD group and normal controls, are reflective of the difficulties experienced by the RD group at the basic word reading level. These results are consistent with the theory that efficient sight word reading and decoding skills are necessary for attentional resource allocation to higher reading processes such as comprehension (LaBerge & Samuels, 1974). The results for reading comprehension for the clinical groups are based on fairly brief narrative passages. Although self-paced silent reading is fairly commonplace in the secondary classroom, the text genre and length may not represent the same reading demands as when the student is required to read a chapter in a biology textbook. The scores, therefore, obtained on the standardized

13 376 K. Ghelani et al. comprehension measures used in this study may be higher than those obtained on curriculum-based assessments. The reading difficulties of the RD groups and the milder difficulties observed in the ADHD group may become exacerbated in situations requiring increased cognitive load (i.e. when required to reading expository passages). The findings, indicating persistent difficulty for the RD groups (RD only and ADHD+RD) across reading accuracy and reading rate measures, are not surprising. The results highlight the significant challenges some adolescents with reading disabilities face. Subtle difficulties were evident for adolescents with ADHD on measures of text reading accuracy and reading rate for words and text. That is, their scores on these measures were within the average range although lower than those of the normal controls and, in some cases, lower than the normative sample mean (i.e. Mean ¼100, SD ¼ 15). These results were maintained for the ADHD group after controlling for reading accuracy, with one exception: rapid nonword reading efficiency scores were no longer significantly different. The latter result is consistent with previous reports of intact phonological processing in the ADHD group (Purvis & Tannock, 1997, 2000; Rucklidge & Tannock, 2002; Willcutt et al., 2001) which remains even with the addition of a speed component. Slower response times on naming tasks for visual stimuli were evident for both the RD group and the ADHD group, although a differential profile of results emerged. The RD group showed a generalized naming deficit for letters, digits, colors, and objects whereas the ADHD group showed impairment only when naming colors and objects. Ancillary analyses indicated that the difference between the two RAN Composites was significant for the ADHD group and marginally significant for the RD group. These results are consistent with previous studies that have identified generalized longer response latencies across naming tasks in the RD group (Wolf & Bowers, 1999; Wolf et al., 2002) and longer response latencies on colors and objects for the ADHD group (Carte, Nigg, & Hinshaw, 1996; Tannock, Martinussen, & Frijters, 2000; Semrud-Clikeman et al., 2000). The literature has highlighted the methodological quandaries that confront the researcher when assessing the effect of IQ (e.g. Kuntsi et al., 2004; Stanovich & Siegel, 1994) on performance, particularly in clinical groups. When the analyses were rerun controlling for IQ, an intriguing differential pattern of results was found for each group. When IQ was controlled, the effect of reading disabilities on most reading tasks (i.e. silent reading comprehension, accuracy, rate, and reading efficiency) remained. This finding is consistent with the literature that indicates that neurocognitive deficits (i.e. reading and language skills) (Willcutt et al., in press) in the RD group cannot be completely explained by individual differences in IQ. When examining whether the original results were upheld for the ADHD group, however, differences between the ADHD group and the normal controls were eliminated when covarying for IQ with two exceptions: reading rate and sight word reading efficiency. The findings that estimated FSIQ did not explain performance on many of the rapid reading tasks for the RD group are similar to those reported by Wolf et al. (2002) for naming speed and IQ. Wolf et al. reported that IQ level is significantly correlated only with phonological measures and not with naming-speed variables. Of note, the differences for the ADHD group on color and object

14 Reading Disability in Adolescents 377 naming were no longer significant after controlling for IQ. Color and object naming have been differentiated in the naming speed literature as being semantically rather than phonologically based (e.g. Wolf & Obreg!on, 1992). The finding for the ADHD group is consistent with a study suggesting that the lexical-semantic demands of rapid naming of colors may require more effortful processing than word reading (Stuss et al., 2001). Recently, evidence has been accumulating suggesting slower processing speeds in individuals with ADHD/IA (Predominantly Inattentive Subtype) (Berninger, Abbott, Billingsley, & Nagy, 2001; Chhabildas, Pennington, & Willcutt, 2001; Rucklidge & Tannock, 2002; Weiler, Bernstein, Bellinger, & Waber, 2000, 2002; Willcutt et al., in press). Results of a recent study suggest that individuals with ADHD/IA process visual information more slowly, particularly in the context of increased cognitive load and a requirement for integrating multiple component operations (Weiler et al., 2000). The clinical sample in this study had a high proportion of inattentive individuals both in the RD groups (RD only and ADHD+RD) and in the ADHD group. The clinical groups experienced varying degrees of naming speed difficulties, with the RD groups (RD only and ADHD+RD) performing more poorly than either the ADHD group or the normal controls. These findings may provide some evidence for naming speed deficits and inattention as potential zones of overlap between these two groups (i.e. RD only and ADHD+RD). These findings may have relevance for our understanding of the reading process. Selective attention is required to effectively perform an operation in the presence of conflicting information (Posner, 1988). Posner and Peterson (1990) theorized that attention is guided, as if it were a spotlight. In order for this guiding to occur, the spotlight must be disengaged, moved, and then re-engaged. The slower and less efficient performance of the ADHD/IA group on measures of naming speed could reflect differences in these operations (Weiler et al., 2000). The process of reading also requires the ability to rapidly shift focus (i.e. from one unit of print to the next; from decoding to comprehension) (LaBerge & Samuels, 1974). Several longitudinal studies have contributed to growing evidence for the link between inattention and reading abilities. McGee, Prior, Williams, Smart, and Sanson (2002) examined outcomes for adolescents who had been diagnosed with hyperactivity early in school. They found that early inattentive behaviors were associated with later inattention and poor reading outcomes in adolescence. Other studies have also documented a pathway from inattentive behavior to poor reading skills (Rabiner & Coie, 2000; Warner-Rogers, Taylor, Taylor, & Sandberg, 2000). In the current study, many of the adolescents with ADHD had previously been diagnosed as having the Combined subtype of ADHD (i.e. both Inattentive and Hyperactive/Impulsive symptoms were elevated) but their restless and impulsive symptoms had diminished over the years. Although still undetermined, the milder reading rate difficulties in the ADHD group may also be reflective of the slower processing speed that has been documented in the ADHD Predominantly Inattentive type (ADHD/IA), and the fact that the majority of our sample belong to this group. The relevance of milder difficulties in reading rate to lower scores in reading comprehension in the ADHD group is unknown. It is unclear whether these mild differences would become exaggerated under other reading conditions (i.e. lengthier passages and expository genre). The current literature suggests that both listening comprehen-

15 378 K. Ghelani et al. sion for expository text may be difficult for the ADHD group (McInnes, Humphries, Hogg-Johnson, & Tannock, 2003). Further research is needed to assess whether different reading conditions produce different patterns of results for this population. Clinical Relevance Findings from the present study have important clinical and educational implications for assessment and intervention, particularly for adolescents with a reading disability (RD only and RD+ADHD) who were impaired across reading measures. This investigation highlights the need to include a number of different reading skill measures when conducting psychoeducational assessments rather than relying solely on measures of untimed isolated sight word reading and decoding. Reading problems for adolescents with reading rate deficiencies are frequently missed on psychoeducational assessments. Reading comprehension tasks that assess reading rate, oral decoding, and prosody, as well as silent reading tasks that reflect classroom reading, should be included in the assessment. There are also limitations to the current standardized reading comprehension measures, however. For example, although the presentation format (i.e. silent reading, multiple-choice questions) of the GSRT is common within the secondary classroom, the content of the GSRT may not be. The narrative passages that are used are relatively short compared to typical passages that are required reading in secondary school texts. In addition, the questions may draw on the reader s background knowledge and allow the reader to infer the correct answers without actually reading the passage. Standardized tests introduce a number of confounds. For example, on the silent reading task, the reader is allowed to refer back to the passage in order to answer the multiple-choice questions unlike the oral reading condition where the text is not available for referral. There is less demand on working memory in the silent passage format. Working memory, which is important for complex cognitive activities (Gathercole & Pickering, 2000), has been documented as being problematic in both RD and ADHD populations (Barkley, 1997; de Jong, 1998; Mariani & Barkley, 1997; Martinussen, Hayden, Hogg-Johnson, & Tannock, in press). A critical lens is necessary to differentiate the cognitive processes required by the various reading tests. A slower reading rate, as evident in the RD groups (RD only and ADHD+RD), presents a severe challenge for the adolescent who is required to read longer passages and increasingly difficult text. Expository passages (i.e. scientific text) demand different cognitive abilities (McInnes et al., 2003) and may place increased demands on working memory and attentional processes, which may, in turn, have a detrimental impact on reading rate. Some adolescents may not be identified as having reading comprehension difficulties in the early grades but, as they face increasingly complex text, their rate inefficiencies may prevent them from keeping pace with the amount of required reading. Slower processing speed has implications for classroom accommodations, particularly the provision of extra time allotments. Extra time provisions are routinely granted to adolescents with learning difficulties as they require more time to decipher print. For the ADHD group, this recommendation has been based on considerations of behavioral symptoms (i.e. the adolescent is easily

16 Reading Disability in Adolescents 379 distracted and therefore needs more time to accomplish his work). For students who have both inattention and reading difficulties, being provided with additional time is important. Recommendations for Intervention The National Reading Panel (NRP, 2000) formed by the National Institute of Child Health and Human Development (NICHD) in the United States rigorously examined the scientific basis for instruction of text comprehension. The report that followed recommended a number of strategies that have been found to be effective in improving reading comprehension. These strategies include approaches such as: comprehension monitoring; teaching metacognitive skills; providing relevant prior knowledge; using graphic organizers to decrease memory requirements; question answering, generation, and summarization; and the use of multiple strategies. The report also emphasized the need for teachers to use an active and directive approach when introducing these strategies. Although there is exciting data indicating that significant improvement can be made in ameliorating phonological reading deficits (Lovett et al., 1994; Lovett, Barron, & Benson, 2003), fluency is often more difficult to remediate (Meyer & Felton, 1999; Wolf & Katzir-Cohen, 2001). Torgesen et al. (2001) found that individuals with reading disorders who have remediated decoding abilities continue to be very slow, nonfluent readers. Chard, Vaughn, and Tyler (2002) conducted a meta-analysis of interventions for increasing reading rate and found that repeated oral reading was critical to improving reading comprehension. Their study also suggested the importance of having a teacher model reading fluency by reading aloud and also the importance of providing the opportunity for rereading text many times to many different people. Reading progressively more difficult text, with feedback and correction for missed words, is essential for improving fluency. Increased practice in fluency can also be supplemented through innovative software programs such as the Kurzweil 3000 TM (Kurzweil Educational Systems, 2000) which allows the struggling reader the opportunity to hear high-interest, low vocabulary material while reading along silently. The benefit of using Kurzweil 3000 TM with post-secondary students with ADHD has been described by Hecker, Elkind, Elkind, and Katz (2002). Study Limitations The authors of this investigation recognize that reading comprehension is a complex activity and that several important cognitive processes that can impact on reading comprehension such as attention, working memory, and linguistic processes were not included in this study. Furthermore, this study did not use reading comprehension measures that might have reflected actual classroom reading tasks such as longer expository passages. This study did not control for comorbid language impairments in the RD group. These impairments may possibly explain this group s pervasive impairment on reading measures. Reading Disability is a very heterogeneous disorder with different subtypes that may or may not include higher order

17 380 K. Ghelani et al. linguistic processing deficits. Another limitation of this study is that most of the sample of ADHD adolescents belonged to the Inattentive type. Many of these adolescents received a childhood diagnosis of Combined subtype but no longer met criteria for that diagnosis. Therefore, our results may not be generalizable to adolescents who are currently diagnosed with the Combined subtype. It would be important to include a larger sample of this subtype in future research to assess whether there are differences in cognitive processing abilities between the Inattentive subtype and the Combined subtype of ADHD. An additional limitation of this study is that many of the normal controls were recruited through referrals from hospital employees. Therefore, the normal comparison group may not be as representative as perhaps a group of adolescents recruited through the same local schools as the clinical groups. Unfortunately many struggling adolescent readers fall further and further behind their normal reading peers. The tragic outcome is that many of these adolescents become completely uninterested in the reading process and may eventually drop out of school. Continued investigation and understanding of the cognitive processes required for reading at this age is critical for the design of appropriate interventions to specifically target areas of weakness. It is only through building a bridge from research to the classroom application that we can hope to help these adolescents become enabled rather than disabled readers. ACKNOWLEDGEMENTS This research was completed as part of a doctoral dissertation by Karen Ghelani, University of Toronto, Toronto, Ontario, Canada. This research was supported by the International Dyslexia Association Research Grant Award 2002 to K. G. and R. T. We would like to acknowledge the contribution of the families who participated in this study. References American Psychiatric Association. (2000). Diagnostic and statistical manual of mental Disorders, 4th edition- text revision. Washington, DC: American Psychiatric Association. Barkley, R. (1997). ADHD and the nature of self-control. New York: Guilford Press. Berninger, V., Abbott, R., Billingsley, F., & Nagy, W. (2001). Processes underlying timing and fluency in reading: Efficiency, automaticity, coordination, and morphological awareness. In M. Wolf (Ed.), Dyslexia, fluency, and the brain (pp ). Timonium, Maryland: York Press, Inc. Bowers, P., & Newby-Clark, E. (2002). The role of naming speed within a model of reading acquisition. Reading and Writing: An Interdisciplinary Journal, 15, Boyle, M. H., Offord, D. R., Racine, Y., Fleming, J. E., Szatmari, P., & Sanford, M. (1993). Evaluation of the Revised Ontario Child Health Study Scales. Journal of Child Psychology and Psychiatry, 34, Bruck, M. (1992). Persistence of dyslexic s phonological awareness deficits. Developmental Psychology, 28, Brock, S., & Knapp, P. (1996). Reading comprehension abilities of children with attentiondeficit/hyperactivity disorder. Journal of Attention Disorders, 1,