Dislexia

Learning Disabilities Research & Practice, 16(3), 152160Copyright C 2001, The Division for Learning Disabilities of the Council for Exceptional Children

The Double-Deficit Theory of Reading Disability Does Not Fit All

Peggy T. Ackerman, Carol A. Holloway, and Patricia L. YoungdahlUniversity of Arkansas for Medical Sciences

Roscoe A. DykmanArkansas Childrens Hospital

The double-deficit theory of reading disability (Wolf & Bowers, 1999) was examined in asample of 56 reading-disabled and 45 normal-reading elementary school children (aged 8 to11). As hypothesized, the two groups differed markedly on all phonological analysis tasksand on rapid continuous naming of digits and letters (the double deficits), but they differedas well on orthographic tasks, attention ratings, arithmetic achievement, and all WISC-IIIfactors except perceptual organization. Within the reading-disabled (RD) sample, children inthe double-deficit subgroup were no more impaired in reading and spelling than those with asingle deficit in phonological analysis, and those with a single deficit in rapid naming wereno more impaired than those with neither deficit. Multiple regression analyses suggest that amultiple causality theory of RD is more plausible than a double-deficit theory.

Numerous reports in the past decade document phonologi-cal impairments in children who experience difficulty learn-ing to read and spell (see reviews by Goswami & Bryant,1990; Pennington, 1991; Wagner & Torgesen, 1987). Manyresearchers consider phonological impairment to be themajor deficit, and a few theorize it may be the only proximalcause of reading failure (Gough & Walsh, 1991; Stanovich,1992; Tunmer & Hoover, 1992). Gough and Walsh (1991)state that children have to learn the cipher (i.e., that soundsmap onto letters) in order to become proficient readers. Theyconcede that children do learn to read perhaps hundreds ofsight words well before they master the cipher, but argue thatit is hard to acquire an adequate reading vocabulary withoutthe cipher. They further posit that word-specific knowledge(needed to pronounce nonphonetic exception words) can beacquired only with the aid of the cipher.

Perhaps the most stringent measure of the cipher is abil-ity to pronounce nonsense words (Goswami, 1993). Indeed, ina large sample of elementary school children with reading orattention disorders, we (Ackerman & Dykman, 1993) found acorrelation of 0.85 (p < 0.001) between number of real wordsand number of nonsense words successfully read. Both realand nonsense word-reading levels were best predicted by thesame set of underlying variables: age and verbal IQ (forcedfirst), plus sensitivity to rhyme and alliteration as measuredby Bradleys (1984) auditory oddity task, continuous namingspeed (Denckla & Rudel, 1976; Wolf, 1991), and an auditoryechoic memory measure (Cohen & Netley, 1981). Thus, ourdata support the Gough and Walsh position in that childrenwho can read short nonsense words can read real words profi-ciently; that is, they have the cipher, to use their term. But,our data further suggest that in order to master the cipher, the

Requests for reprints should be sent to Peggy T. Ackerman, C.A.R.E.Unit, Department of Pediatrics, Arkansas Childrens Hospital, 800 MarshallStreet, Little Rock, AR 72202.

child must have auditory phonological sensitivity as well asother skills. One of these skills is rapid naming.

Our interest in studying continuous naming speed deficitsin reading-disabled children stemmed from the pioneeringwork of Denckla and Rudel (1976) and from the impressivebody of research by Wolf, Bowers, and colleagues (Bowers,Sunseth, & Golden, 1999; Bowers & Wolf, 1993; Wolf, 1991;Wolf & Bowers, 1999; Wolf, 1999; Wolf & Obregon, 1992;1995) and by Spring and his associates (Spring & Capps,1974; Spring & Davis, 1988; Spring & Perry, 1983). Bowersand Wolf (1993) were the first to propose the double-deficittheory of reading disability. They report that children withboth phonological and rapid naming deficits are the poorestreaders, but those with either deficit are less proficient thanchildren who are fast continuous namers and phonologicallycompetent.

Although some investigators (e.g., Wagner & Torgesen,1987) have viewed continuous naming speed as a measureof phonological competence, we have found only a modestcorrelation between naming speed and phonological sensitiv-ity to rhyme and alliteration (Ackerman & Dykman, 1993).Baddeley (1986) had proposed that a slow articulation ratecould be the overarching determinant of both slow nam-ing and impaired phonological sensitivity, but our findings(Ackerman & Dykman, 1993) did not support this theory.Rather, our data support Bowers and Wolf (1993) in show-ing that both naming speed and phonological skill account forunique variance in word-list reading level. However, our find-ings suggest there may be more than two contributory factors.

This is also the position of Badian (1997), whose studiesimplicate visual matching of alphanumeric stimuli (i.e.,orthographic processing). Further, the studies of Meyer,Wood, Hart, and Felton (1998) suggest that poor rapidnaming alone is not sufficient to cause chronic poor reading.Yet if investigators choose to study rapid naming or codingor any of several other measures of processing speed, they

LEARNING DISABILITIES RESEARCH 153

will almost without exception find a significant differencebetween groups of normal and disabled readers (Ackerman& Dykman, 1996; Dykman & Ackerman, 1991; Fawcett &Nicholson, 1994; Tallal, Miller, & Fitch, 1993; Wolff, Ovrut,& Drake, 1990).

The present study was undertaken to look at the relativecontributions of phonological analysis and rapid namingto literacy acquisition in normally intelligent elementaryschool children. It was assumed, however, that these twoabilities would not be sufficient to explain all instances ofreading failure, and, given our past research history, weparticularly wished to evaluate the effects of attentionalproblems, arithmetic acquisition, and cognitive abilities.The cognitive abilities of greatest interest to us are thosetapped by the once clinically popular ACID pattern subtestsof the Wechsler Intelligence Scale for Children (Arithmetic,Coding, Information, Digit Span). These subtests challengeshort-term, long-term, and working memory, as well asspeed of mental processing, and are frequently depressed inlearning-disabled children (Ackerman, Dykman, & Peters,1977; Dykman & Ackerman, 1991; Swartz, 1974).

We hypothesized that our samples of normal and disabledreaders would be robustly separated on measures of phono-logical analysis, naming speed, attention, verbal skills, short-term and working memory, and arithmetic achievement. Wealso hypothesized that children with multiple deficits wouldbe the most retarded readers. As a corollary we assumedthat children will vary in degree of impairment on under-lying abilities and that multiple regression analyses wouldtherefore explain literacy skill differences better than catego-rization.

Finally, we wished to see whether there are orthographicskills that are separable from phonological skills and thusmight identify children who are poor readers and spellersdespite phonological analysis strengths.

METHOD

Participants

Two groups of elementary school children (aged 8 to 11)served as participants. The reading-disabled (RD) group(N = 56) included 23 Caucasian boys, 13 African-Americanboys, 17 Caucasian girls, and 3 African-American girls. Thenormal-reading (NR) comparison group (N = 45) included25 Caucasian boys, 2 African-American boys, 13 Caucasiangirls, and 5 African-American girls.

The reading-disabled children were referred to the projectfrom several sources: The Child Psychiatry and the DennisDevelopmental Clinics at Arkansas Childrens Hospital(ACH), local child psychologists, and local schools. Lettersdescribing the project were mailed to all these sources andreferrals were invited. The control children were recruitedvia advertisements placed on bulletin boards at ACH.

All children considered for selection had to be in goodhealth with no limiting physical disabilities, and they hadto have had normal schooling opportunities. Additionally,all had to speak English as a first language. Parents signed a

consent form approved by our Internal Review Board and thechildren freely gave their assent. Parents were compensated$50 and children $10. Meal tickets were provided for lunchat the ACH cafeteria.

Prior to acceptance into the project, all children weregiven the Wechsler Intelligence Scale for Children-III(WISC-III) and the basic reading, spelling, and numericaloperations subtests of the Wechsler Individual AchievementTest (WIAT). Those accepted into either group achievedeither a Full Scale or Verbal IQ of 85 or higher. The childrendesignated as normal readers (NR) had standard scores of90 and higher on the WIAT reading and spelling subtests.Those designated as RD had standard scores of 86 or loweron one or both subtests. The Wide Range Achievement TestRevision-3 (WRAT-3) was given to obtain confirmatory data.

Behavioral Data

Subjects were not excluded for a known or suspected diag-nosis of Attention Deficit Hyperactivity Disorder (ADHD).However, any child taking stimulant medication was requiredto omit the medication on the day of testing. The accompany-ing parent was asked to complete the Child Behavior Check-list (Achenbach, 1991) and an ADHD questionnaire adaptedfrom DSM-IV. The questionnaire listed 18 symptoms, withseverity of each to be rated on a 4-point scale (0 = not aproblem, 1 = just a little, 2 = pretty much, 3 = very much).The first 9 items assessed problems with attention, the next 5assessed overactivity, and the last 4 impulsivity.

Phonological Awareness Battery

1. An abbreviated (13 item) form of the Test of Audi-tory Analysis Skills (TAAS) (Rosner & Simon, 1971),recently used by other investigators (Badian, 1996;1997; Fawcett & Nicolson, 1995). Each word is pro-nounced by the examiner who then instructs the childto repeat the word, then to repeat it again but to omita specified sound. On the first of two demonstrationtrials, the examiner says cowboy and then asks thechild to repeat the word and then repeat the word with-out boy. Then follows steamboat. Test words arearranged in order of difficulty, and testing is discon-tinued after 4 consecutive errors. The examiner pro-nounces the specific sound to be omitted and not theletter name(s). For example, item 4 is coat with thekuh sound omitted. Badian (1997) reported a testretest reliability coefficient of 0.84 for this task.

2. Bradleys (1984) Auditory Sound Categorization Test.The Bradley Test consists of 24 series of 4 wordseach, wherein 1 word does not sound like the other3. Sixteen of the trials involve rhyme judgment and 8require detection of alliteration. Normal readers havenear perfect scores on this task by age 8 or 9 (Bradley,1984).

3. Pig-Latin Test (Olson, Wise, Conners, & Rack, 1989).The subject is asked to segment the initial phoneme

154 ACKERMAN ET AL.: DOUBLE-DEFICIT THEORY

from spoken words, place the phoneme at the endof the word, add the sound ay, and pronounce theresult. Thus, pig becomes ig-pay; dog becomes og-day; bird becomes ird-bay; etc. Following 5 trainingtrials, wherein the examiner demonstrated what wasto be done to each word, 20 such 1-syllable wordswere presented. The examiner provided the correctanswer if the child erred. Testing was discontinued ifthe child erred 5 times in a row.

4. Rhyme Fluency Test. Fluency was assessed with arhyme-generation task (Olson et al., 1989). Four stim-ulus words (eel, ate, cat, kite) were used and the chil-dren were asked to name as many words as they couldthat rhymed with each (1 minute per trial). The exam-iner illustrated by giving rhymes to and.

Phonological Decoding

The 1- and 2-syllable pseudoword lists of the Decoding SkillsTest (Richardson & DiBenedetto, 1985) were given to eachchild. The child sees a series of cards with 5 pseudowords oneach card and is asked to pronounce each item. There are 301-syllable and 30 2-syllable items. Testing is discontinued oneach list when the child makes 5 consecutive errors.

Orthographic Skills

Four tests assessed the childrens recognition of written or-thographic patterns.

Part 1 of a written test of rhyme recognition utilized or-thographically similar (regular) word-word or word-nonwordpairs (for example cat, hat; fat, zat), 20 of each type. Foilswere orthographically similar but nonrhyming words (e.g.,cat, car) and nonwords (fat, fav), 20 of each type. Thecompletely randomized list was presented to the child and heor she was asked to highlight the pairs that rhymed. In PartII of the rhyme-recognition test, the word-word pairs wereorthographically dissimilar; 20 rhymed (e.g., blue, new) and20 did not (e.g., rows, hole). The children were given asmuch time as they needed to complete these tests.

Another task assessed spelling recognition. Ten gradedlists of 10 stimulus trials were used. The lists sampled frompreprimer, primer, and 1st- to 7th-grade master lists. Thechild was asked to highlight the real word in each trial. Onefoil was a phonologically legitimate spelling of the real word(a pseudohomonym) and the other foil was not. For example,a trial from the 1st-grade list was room, rume, ruom; a trialfrom the 4th-grade list was blays, blaze, blais. Testing wasdiscontinued at the level where the child got fewer than 5correct answers.

A second spelling test assessed the childs ability to spellirregular words relative to regular words at his or her spellinglevel ability. The word lists of the Boder-Jarrico Test (1982)were used here. If a childs spelling grade level on theWIAT was grade 2, for example, we asked the child towrite the spellings of 10 words from the grade 2 readinglist; 5 were phonetically regular words and 5 were irregularwords.

Rapid Automatized Naming (RAN)

Three types of stimuli were presented to the children forrapid naming: digits only, letters only, and alternating digitsand letters. The children saw 50 stimuli (5 columns and 10rows) on each 5- by 7-inch card. They were asked to readthe stimuli aloud (row after row) as rapidly as possible.The children were given the numbers card first, the letterssecond, and the alternating list last. The examiner used astopwatch to time each trial.

RESULTS

The reading-disabled (RD) and normal-reading (NR) groupswere well matched for age. As is usually the case in referredRD samples, male children outnumbered females almost 2to 1. The ratio of Caucasian to African-American childrenwithin the RD group was 2.5 to 1, which is reflective of theregional population ratio for school-age children. The genderand race composition of the NR group is similar to that ofthe RD group except that African-American boys comprisea higher percentage of the RD than NR group (23% versus4%).

Preliminary analyses (ANOVAs) of selection variablesevaluated possible gender and race differences and inter-actions within the group. No significant interactions werefound. African-American (AA) children scored significantlylower on WISC-III Verbal, Performance, and Full Scale IQs(F1, 93 = 16.46, 6.98, and 16.76, respectively, p < 0.01 foreach). Mean differences for the three IQs were 12.6, 8.3,and 11.4 points. Boys had significantly higher PerformanceIQs than girls (F1, 93 = 4.12, p = 0.045): 102.2 (12.0) versus98.7 (12.7). Reading and spelling standard scores from theWIAT and WRAT-3 were somewhat lower for AA childrenbut differences were not significant. There were no genderdifferences on the reading and spelling tests.

IQ and achievement test group differences (with genderand race ignored) are given in Table 1. Since the groups wereselected to differ in reading and spelling, the large mean dif-ferences are as expected. Given a substantial correlation in theWIAT and WRAT-3 standardization samples between arith-metic and reading/spelling scores, it is predictable that theNR and RD groups would also differ in arithmetic scores.

Three of the four WISC-III factor scores and the ACID pat-tern (Arithmetic, Coding, Information, Digit Span; Swartz,1974) separated the groups.

Table 2 presents behavioral rating scores for the twogroups. Given the high level of comorbidity of ADHD andlearning disabilities (Dykman & Ackerman, 1991), it was tobe expected that the RD group would have more adverse rat-ings on both the Child Behavior Checklist and the ADHDrating scale. In mixed model ANOVAs of these behavioralratings, race and gender did not emerge as significant fac-tors.

As predicted, all the oral tests in the phonological skillsbattery significantly separated the two groups (see Table 3).Also, as expected, the Decoding Skills Test, requiring cor-rect phonological pronunciation of pseudowords, providedthe most robust group differences.


TABLE 1Demographic and Selection Measures: Group Means and Standard

Deviations (SD)

Reading Disabled Normal Reading

(N = 56 ) (N = 45 )Measure Mean SD Mean SD t(99df)

Age (months) 116.6 8.3 115.8 8.1 0.48WISC-III

Verbal IQ 94.3 10.3 106.9 12.3 5.58Performance IQ 97.6 11.0 105.0 12.8 3.15Full Scale IQ 95.4 9.3 106.3 11.9 5.18Verbal 95.3 10.7 106.8 12.5 4.97

ComprehensionPerceptual 99.4 11.9 103.9 14.2 1.73

OrganizationuFreedom from 90.4 9.9 103.5 12.4 5.75

DistractibilityPerceptual Speed 98.6 12.0 108.2 11.8 3.98ACID pattern 33.1 6.2 43.5 6.8 8.06

WIATuReading ss 79.7 7.0 103.6 12.4 11.51uSpelling ss 79.5 7.3 101.8 14.1 10.20Arithmetic ss 92.4 10.4 102.2 11.2 4.56

WRATuReading ss 76.9 9.6 101.3 12.8 10.63uSpelling ss 78.7 7.2 100.3 14.5 9.13Arithmetic ss 90.2 11.8 102.5 10.2 5.53

Note. SS = standard scores, u = unequal variances, p < 0.05,p < 0.01, p < 0.001.

The tests of orthographic skills likewise significantly sep-arated the groups (see Table 4), as did the Rapid AutomatizedNaming tasks (Table 5).

RD Subgroup Analyses

A primary reason for this study was to compare thereading spelling performance of RD children with single-versus double-deficit profiles. To that end, we created foursubgroups using performance on the oral TAAS, Bradley,and Pig Latin tests to define a phonological deficit and per-

TABLE 2Behavioral Data: Group Means and Standard Deviations

Reading Disabled Normal ReadingChild BehaviorChecklist Mean SD Mean SD t

Total ss 59.8 11.5 50.8 11.0 4.03Internalizing ss 57.7 12.1 52.9 11.6 2.01uExternalizing ss 56.3 13.1 48.6 10.3 3.31ADHD

Attention sum 15.8 6.3 8.5 7.4 5.25Hyperactivity &

Impulsivity sum 11.7 8.2 6.0 5.8 4.11

Note. ss = standard scores, u = unequal variances, ADHD = AttentionDeficit Hyperactivity Disorder, p < 0.05, p < 0.01, p < 0.001.

TABLE 3Phonological Skills: Group Means and Standard Deviations


Mean SD Mean SD t(99df)

Test of Auditory 3.93 1.92 1.96 1.73 5.37Analysis (errors)

uBradley Sound 5.50 4.22 1.69 1.98 5.99Categorization(errors)

uPig Latin (correct) 10.86 7.51 16.73 5.69 4.47Rhyme Generation 15.88 7.32 22.60 8.74 4.21

(correct)Decoding Skills I 8.33 5.83 21.89 5.67 11.76

(correct)uDecoding Skills II 3.66 3.77 16.53 7.26 10.78

(correct)

Note. u = unequal variances, p < 0.001.

TABLE 4Orthographic Skills: Group Means and Standard Deviations (SD)



uRhymes O+ (errors) 7.30 9.44 4.27 5.86 1.98Rhymes O (errors) 12.29 4.00 4.47 3.91 9.86uSpelling Detection 44.20 22.71 78.53 14.86 9.14

(correct)Spelling, Regular 3.14 1.15 3.80 1.08 2.93

(correct)Spelling, Irregular 1.41 1.44 2.67 1.22 4.63

(correct)

Note. O+ = orthographically similar, O = orthographically dissimi-lar, u = unequal variances, p < 0.05, p < 0.01, p < 0.001.

formance on the RAN tests to define a naming speed deficit.Error scores of 4 or higher on the TAAS, 5 or higher on theBradley, and 8 or more on the 20 Pig Latin items are con-sidered suspect for children in the age range here studied,judging from prior studies comparing normal and disabledreaders (Badian, 1997; Bradley, 1984; Olson et al., 1989).Thus, we elected to classify a subject as phonologically im-paired if his or her error scores on two of the three testsreached these cut-scores. Rhyme fluency was not used in thisclassification algorithm since it does not as directly assess theability to break words into component sounds.

TABLE 5Rapid Automatized Naming



uDigits (sec) 35.6 10.4 24.8 5.9 6.57Letters (sec) 40.5 10.5 29.5 7.5 5.98uAlternating (sec) 50.4 15.8 35.7 9.3 5.85

Note. u = unequal variances, sec = seconds, p < 0.001.


TABLE 6Phonological and Rapid Naming Values for RD Subgroups

Neither Slow Phono BothN = 18 N = 13 N = 9 N = 16 F3,52 p Pairwise

TAAS errors 2.7 2.8 5.7 5.3 18.44 3 = 4WIAT Spell ss 83.3 80.4 75.8 76.7 3.76 0.016 1 > 3,4; 1 = 2WRAT Read ss 81.8 80.6 72.8 70.6 6.52 0.001 1 = 2 > 3 = 4WRAT Spell ss 81.4 80.2 75.2 76.3 2.53 0.067 1 > 3,4; 1 = 2Literacy Sum 329.4 322.7 300.6 299.9 5.81 0.002 1 = 2 > 3 = 4Decoding Skills 18.5 16.4 3.8 5.8 19.96 3 = 4

Note. WISC = Wechsler Intelligence Test for Children, ACID = WISC Arithmetic + Coding + Information + Digit Span, WIAT = Wechsler IndividualAchievement Test, WRAT = Wide Range Achievement Test, ss = Standard Scores.

The subgroups did not differ on other WISC-III factors,or on CBCL or ADHD ratings. Nor did they differ on theorthographic tasks listed in Table 4.

Regression Analyses

The above subgroup analyses did not reveal the hypothesizedincremental deficiencies in reading and spelling scores at-tributable to dual underlying deficits in phonological analysisand naming speed. The slow only subgroup was no moreimpaired than the neither subgroup, and the dual-deficit(both) subgroup was no more deficient than the phono-logical only subgroup. Still, in the sample as a whole bothphonological and naming deficits as well as other factors sep-arated the NR and RD groups. Thus, we opted to use stepwiseregression analyses to better understand the data.

In order to limit the number of independent variablesentering into these analyses, we computed a single factorscore for the phonological variables, which were all highlyintercorrelated, and we computed a single RAN measure(the sum of seconds on the three subtests). In addition tothe WISC-III Verbal Comprehension factor scores, we in-vestigated the ACID factor (arithmetic, coding, information,and digit span) because of its discriminating power in earlierstudies of learning-disabled children (Ackerman et al., 1977).Other independent variables included the ADD index andWRAT-3 arithmetic standard scores. Race and gender wereincluded in initial exploratory analyses but were not foundto explain any significant variance. The same was the case


TABLE 8Correlation Matrix and Factor Loadings

1 2 3 4 5 6 7 8 Loadings on Factor I

1. Literacy Sum 0.9232. Decoding Skills Sum 0.886 0.8643. ADD Index 0.576 0.490 0.6494. ACID factor 0.755 0.650 0.538 0.8925. WISC Verbal Factor 0.605 0.567 0.306 0.756 0.7426. Phonological Factor 0.703 0.777 0.406 0.606 0.574 0.8017. RAN Sum 0.594 0.528 0.433 0.560 0.345 0.519 0.6868. WRAT Arithmetic 0.671 0.505 0.459 0.760 0.517 0.451 0.429 0.758

Note. ADD = Attention Deficit Disorder, ACID = WISC Arithmetic + Coding + Information + Digit Span, WISC = Wechsler Intelligence Scale for Chil-dren, RAN = Rapid Automatized Naming, WRAT = Wide Range Achievement Test. All correlation coefficients are significant at p < 0.01 or higher.

for hyperactivity ratings and internalizing and externalizingscores from the CBCL. For dependent measures we used thesum of correct responses on the Decoding Skills Tests andthe sum of standard scores on the WIAT and WRAT-3 read-ing and spelling tests (labeled literacy sum). Intercorrelationsof these dependent and independent variables are given inTable 8. Principal components factor analysis of these vari-ables yielded only one factor with an eigenvalue > 1.0. Load-ings are shown in the last column.

The first set of regression analyses used the entire sample.Decoding Skills Test (DST) scores and reading/spellingscores are generally robustly correlated (Ackerman &Dykman, 1993), which was the case here (R = 0.886,

TABLE 9Regression Analyses: Entire Sample

Dependent R R2 Final Beta Weight

I. Decoding Skills SumStep 1. Phonological factor 0.777 0.603 0.605Step 2. ACID factor 0.809 0.654 0.284

II. Decoding Skills SumStep 1. Phonological factor 0.777 0.603 0.606Step 2. ADD index 0.800 0.639 0.195Step 3. Verbal comprehension 0.810 0.656 0.160

I. Literacy SumStep 1. ACID factor 0.755 0.571 0.271Step 2. Phonological factor 0.816 0.666 0.368Step 3. ADD index 0.832 0.693 0.181Step 4. WRAT arithmetic 0.844 0.713 0.216

II. Literacy SumStep 1. Phonological factor 0.703 0.494 0.317Step 2. WRAT arithmetic 0.807 0.652 0.285Step 3. ADD index 0.830 0.689 0.195Step 4. RAN sum 0.841 0.707 0.169Step 5. Verbal comprehension 0.850 0.722 0.157

III. Literacy SumStep 1. Decoding skills 0.886 0.785 0.662Step 2. WRAT arithmetic 0.923 0.852 0.283Step 3. RAN sum 0.928 0.861 0.096Step 4. ADD index 0.931 0.867 0.094

Note. ADD = Attention Deficit Disorder, ACID = WISC Arithmetic +Coding + Information + Digit Span, WISC = Wechsler Intelligence Scalefor Children, RAN = Rapid Automatized Naming, WRAT = Wide RangeAchievement Test. All correlation coefficients are significant at p < 0.01 orhigher.

p < 0.01). An obvious initial question is how well theindependent variables predict the DST scores. Table 9 sum-marizes these analyses. Only the phonological factor scoresand the ACID factor scores were accepted to achieve a robustR of 0.81 (p < 0.000). If the ACID factor is not included inthe regression for DST, the ADD and Verbal Comprehensionfactors are accepted along with the phonological factor toyield a virtually identical R (0.810). If the ADD index is notincluded, the WRAT-3 arithmetic score is chosen in Step 2to yield an R of 0.792. The RAN variable enters only if theACID, ADD, and arithmetic measures are excluded. Then,it is taken third after the phonological factor and VerbalComprehension to yield an R of 0.799.

Next the literacy sum scores were predicted, excludingDST scores. In addition to ACID and phonological factorscores, ADD and WRAT arithmetic scores were accepted toyield an R of 0.844 (p < 0.000). If ACID is not allowed to en-ter, the solution is as shown for Literacy Sum II. When DST isallowed to enter in the prediction of literacy sum (see exampleIII), the phonological factor drops out but WRAT arithmeticand ADD remain along with RAN to yield an R of 0.931(p < 0.000). If only the phonological and RAN variablesare allowed to enter, R is only 0.753, with the phonologicalfactor explaining 49% of the variance and RAN adding 7%.

A second set of multiple regression analyses was limitedto the RD group. At issue here is the degree of reading/

TABLE 10Regression Analyses: RD Group

Dependent R R2 Final Beta Weight

I. Decoding SkillsStep 1. Phonological Factor 0.773 0.597 0.773

I. Literacy SumStep 1. Phonological Factor 0.615 0.378 0.535Step 2. WRAT Arithmetic 0.742 0.551 0.424

II. Literacy SumStep 1. Phonological Factor 0.615 0.378 0.287Step 2. WRAT Arithmetic 0.742 0.551 0.458Step 3. Decoding Skills 0.768 0.590 0.313

Note. ADD = Attention Deficit Disorder, ACID = WISC Arithmetic +Coding + Information + Digit Span, WISC = Wechsler Intelligence Scalefor Children, RAN = Rapid Automatized Naming, WRAT = Wide RangeAchievement Test. All correlation coefficients are significant at p < 0.01 orhigher.


spelling impairment, which ranges from mild to severe. Theliteracy sum scores for the RD children ranged from 231to 357 (SD = 27.0), and the Decoding Skills (DST) sumranged from 0 to 32 (SD = 8.7). Table 10 summarizes theseanalyses. The DST sum is predicted only by the phonologicalfactor. The literacy sum is predicted by the phonologicalfactor and the WRAT arithmetic scores (R = 0.742). Ifthe literacy sum independent variables list includes DSTscores, the phonological factor scores are taken as step 1because they were more strongly correlated with literacysum than the DST (0.615 versus 0.553). However, thebeta weight for the DST was somewhat higher in the finalsolution.

The orthographic tasks formed a single factor that wasso robustly correlated with reading and spelling standardscores and the phonological factor and DST scores as to castdoubt on its use as an independent variable. Rather, this factorappears to tap phonological as much as orthographic ability(see Velutino, Scanlon, & Chen, 1995, on this issue).

Follow-Up Analyses of RAN

Because the subgroup and regression analyses did not showas adverse effect of slow naming as expected, we performedseveral post hoc exploratory analyses with RAN scores to tryto discover why our findings are not strongly supportive ofthe double-deficit theory.

Even in our first major study to combine RAN and phono-logical variables, we had to include Verbal IQ and a test ofshort-term memory in order to achieve a robust multiple Rin the prediction of reading level (Ackerman & Dykman,1993). The current model (Table 9) incorporating ACID pat-tern scores, standardized arithmetic scores, and ADD ratingsprovides an even better fit. Examination of Table 8 offers atleast a partial explanation. Note that RAN scores are sig-nificantly related to ACID scores (0.56) and phonologicalscores (0.52), which have the highest correlations with lit-eracy sum. Of the four WISC subtests making up the ACIDpattern, RAN times are most strongly correlated with Coding(0.50, p < 0.001) but each of the other associations are alsosignificant (Arithmetic, 0.41; Information, 0.40, and DigitSpan 0.34, all p = 0.001). When RAN sum was includedwith all the WISC subtests in a principal components fac-tor analysis, its loading was 0.71 on a presumed perceptualspeed factor with Coding (0.78) and Symbol Search (0.70).Information, Arithmetic, and Digit Span had high loadingswith the other Verbal subtests. Thus, ACID scores appear tooffer a good estimate of academic aptitude because of theinclusion of measures of long-term, short-term, and workingmemory, as well as speed of processing. RAN is not as inclu-sive a measure as ACID, but does appear to measure speedof mental processing just as well as Coding (see Ackerman& Dykman, 1996).

Earlier we had found that RAN scores were not as charac-teristic of garden variety (non-IQ discrepant) poor read-ers as of discrepant poor readers (Ackerman & Dykman,1993; Ackerman, Weir, Metzler, & Dykman, 1996). With thepresent RD children, we created two RAN groups (mediansplit at 116 seconds), and looked at the differences between

Verbal IQ scores and reading and spelling standard scores(averaged for the WIAT and WRAT-3). The faster namershad higher Verbal IQs (96.3) but no larger gap between IQsand reading and spelling (16 and 15, respectively) than theslower namers (IQ = 92.7, gap = 16 for both reading andspelling).

The current RD sample includes more girls and moreAfrican-American children than our past studies, but wefound no gender or race differences in mean RAN scoresand no interactions with group. Age was not significantlycorrelated with RAN scores. The RD sample also includes alarge number of children with attention problems, but slowand fast namers (median split) did not differ on the ADDindex.

RAN has been hypothesized to relate to orthographic pro-cessing, but within our RD sample the slower and fasternamers (median split) did not differ significantly on any ofour orthographic tasks. The slow namers had virtually iden-tical reading and spelling standard scores (77 and 78) as didthe faster namers (80 for both). Thus, the slow namers werenot more impaired in spelling than reading.

DISCUSSION

Insofar as differentiating normal and disabled readers, thisstudy successfully replicated other studies from our labora-tory and from other RD investigators. As expected, the RDand NR groups clearly differed on oral word analysis skillsand on rapid naming speed. They also differed on parentalratings of attention and behavioral problems and on three ofthe four WISC III factor scores as well as the once clinicallypopular ACID factor (Swartz, 1974; Ackerman et al., 1977;Frederickson, 1999). Although selected for reading/spellingdeficits, the RD group was also impaired in arithmetic. Thecomorbidity of attention disorder and RD has often been re-ported (Dykman & Ackerman, 1991; Willcutt & Pennington,2000) as has the comorbidity of reading/spelling and arith-metic disabilities (Ackerman & Dykman, 1995). While read-ing disabilities and attention disorders occur at all levels ofintelligence, it is nonetheless the case that referred and/orrecruited samples of RD children generally have somewhatlower IQs and higher levels of attention problems than stan-dardization samples. Likewise, samples of ADHD childrengenerally have somewhat lower IQs and achievement scoresthan standardization samples.

A primary reason for the current study was to assess pos-sible additive effects of impaired oral word analysis (phono-logical) skill and slow continuous naming on degree of read-ing/spelling impairment. This question was addressed firstby subgrouping and then by stepwise multiple regressionanalysis. The subgrouping maneuver revealed, as expected,that those RD children with phonological deficits read andspelled worse than those without serious phonological defic-its. However, there was no evidence of an additive effect ofslow naming. Rather, the RD children with double defic-its read and spelled no worse than those with a phono-logical deficit only, and the children with a single deficitin naming performed no worse than those with neitherdeficit.


The various multiple regression analyses likewise failedto show much of an adverse impact from slow naming whenother contributory variables were considered. RAN scoreswere robustly correlated with literacy sum (reading plusspelling from the WIAT and WRAT-3) but explained only7% of additional variance once the phonological factor en-tered. The ACID factor and WRAT-3 arithmetic scores weremuch stronger predictors when taken with the phonologicalscores. Within the RD group, once the phonological factorwas accepted, the RAN sum did not enter in the predictionof literacy sum.

Our failure to find strong support for the phonologi-cal/naming speed double-deficit theory of reading disabil-ity may, of course, simply be attributable to the vagaries ofsampling. But, it could also be that the lesson of the blindmen and the elephant is being ignored by some investiga-tors (but see Wolf & Bowers, 1999, pp. 422423). Let us as-sume that rapid naming of alphanumeric stimuli is an indexof speed of mental processing and resistance to mental fa-tigue during continuous processing, both necessary to goodworking memory. Evidence of this comes from significantcorrelations of RAN sum with three WISC subtests: Cod-ing (0.498, p < 0.001), Arithmetic (0.409, p < 0.001), andDigit Span (0.335, p < 0.001). RAN times are also corre-lated with Information (0.403, p < 0.001) and Vocabulary(.324, p = 0.001), suggesting association with the g fac-tor. Additionally, RAN times are correlated with ADD in-dex scores (0.433, p < 0.001), and with Arithmetic achieve-ment scores (0.420, p < 0.001) as well as with Readingand Spelling achievement scores (0.602 and 0.553, respec-tively, p < 0.001 for each).

Our regression analyses suggest there are multiple deficitsunderlying literacy acquisition and that rapid naming is asso-ciated with several of these. However, other measures, suchas the ACID factor, the ADD index, and Arithmetic achieve-ment, provided stronger associations with literacy acquisitionthan RAN times. Also RAN times and the phonological factorwere not independent (R = 0.52).

Two puzzling questions arise from, but are partially an-swered by, our regression analyses. First, why is it that thereare children who have normal oral phonological analysisskill and are adequate namers (the neither subgroup) yet arepoor readers? What weaknesses do they exhibit? Secondly,why are there children who exhibit deficits common to poorreaders yet who read at age-expected levels? How do theycompensate?

To address the first question, in the neither RD sub-group (N = 18), all except 6 had either low ACID scores(116 seconds), 4with phonological deficits only, and 1 with both deficits. Noneof these NR children with naming or phonological deficits hadACID scores


(Retrieval, Automaticity, Vocabulary, Elaboration, Orthogra-phy) can produce positive results.

NOTE

This research was supported by Grant 5R01 HD34182 fromthe National Institute of Child Health and Human Develop-ment and by Arkansas Childrens Hospital Research Insti-tute. We are grateful to coworkers Nancy B. Stewart, ShaneEilts, and Dannette Rook for their help in data collectionand manuscript preparation. We are also grateful to JeanetteMcGrew, Dr. Larry Clarke, Dr. Glen Lowitz, and local ele-mentary school principals for help in recruiting reading dis-abled participants.

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