chapman, 1991

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Journal of Speech and Hearing Research, Volume 34, 1106-1120, October 1991 Language Skills of Children and Adolescents With Down Syndrome: I. Comprehension Robin S. Chapman Scott E. Schwartz Elizabeth Kay-Kaining Bird University of Wisconsin-Madison This study investigates the development of vocabulary and syntax comprehension skills cross-sectionally in 48 children and adolescents with Down syndrome (Trisomy 21), aged 5 20 years, in comparison to 48 control children aged 2-6 years matched statistically for nonverbal mental age and mother's years of education. Age-equivalent scores on vocabulary (PPVT-R) and syntax (TACL-R) comprehension tests differed in the Down syndrome group but not the control group; vocabulary comprehension was relatively more advanced than syntax Age- equivalent scores on nonverbal cognitive subtests of pattern analysis and short-term memory for bead arrangements (Stanford-Binet, 4th ed.) also differed for the Down syndrome group but not the control group, indicating an unusual pattern of nonverbal cognitive function in the Down syndrome group. Stepwise multiple regression analyses showed that chronological age and mean mental age, collectively, accounted for 78% of the variability in vocabulary comprehension and 80% of the variability in syntax comprehension in the Down syndrome group, with total passes on a hearing screening accounting for an additional 4% in each case Implications for research are discussed KEY WORDS: Down syndrome, language disorders, comprehension, mental retardation, language development Studies of children and adolescents with Down syndrome (DS) have frequently indicated problems in expressive language development greater than one might expect on the basis of cognitive delay in nonverbal domains or comprehension skill (Andrews & Andrews, 1977; Bray & Woolnough, 1988; Cardoso-Martins, Mervis, & Mervis, 1985; Cornwell, 1974; Dodd, 1975; Gibson, 1978; Greenwald & Leonard, 1979; Harris, 1983; Hartley, 1986; Hill & McCune-Nicolich, 1981; Holdgrafer, 1981; Mahoney, Glover, & Finger, 1981; Miller, 1987, 1988; Mundy, Sigman, Kasari, & Yirmiya, 1988; Rogers, 1975; Rohr & Burr, 1978; Rosin, Swift, Bless, & Vetter, 1988; Smith & Tetzchner, 1986; Wiegel-Crump, 1981). Much less consistent is any report of problems in language comprehension, although the frequent middle ear infections and hearing loss experienced by many of the children (Brooks, Wooley, & Kanjilal, 1972; Dahle & McCollister, 1986) might lead one to expect consequent delays in language comprehension. Among mentally retarded children In general, specific deficits in comprehension, over and above cognitive delay in nonverbal problem-solving domains, are encountered frequent- ly-in 25% (Miller, Chapman, & Bedrosian, 1978) to 60% (Abbeduto, Furman, & Davies, 1989) of the sample. For children with Down syndrome, few studies of language comprehension relative to nonverbal cognitive level exist, and the findings are inconsistent. Hartley (1982) finds poorer performance on syntactic comprehension tasks in children with Down syndrome than in children with mental retardation of other origin, matched on vocabulary comprehension. Within the Down syndrome group, poorer performance is © 1991, American Speech-Language-Hearing Association 1106 002 2-4685/91/3405-1106$0 1.00/0 Downloaded From: http://jslhr.pubs.asha.org/ by a Western Michigan University User on 01/28/2015 Terms of Use: http://pubs.asha.org/ss/Rights_and_Permissions.aspx

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Page 1: Chapman, 1991

Journal of Speech and Hearing Research, Volume 34, 1106-1120, October 1991

Language Skills of Children andAdolescents With Down Syndrome:I. Comprehension

Robin S. ChapmanScott E. Schwartz

Elizabeth Kay-Kaining BirdUniversity of Wisconsin-Madison

This study investigates the development of vocabulary and syntax comprehension skillscross-sectionally in 48 children and adolescents with Down syndrome (Trisomy 21), aged 5 20years, in comparison to 48 control children aged 2-6 years matched statistically for nonverbalmental age and mother's years of education. Age-equivalent scores on vocabulary (PPVT-R)and syntax (TACL-R) comprehension tests differed in the Down syndrome group but not thecontrol group; vocabulary comprehension was relatively more advanced than syntax Age-equivalent scores on nonverbal cognitive subtests of pattern analysis and short-term memory forbead arrangements (Stanford-Binet, 4th ed.) also differed for the Down syndrome group but notthe control group, indicating an unusual pattern of nonverbal cognitive function in the Downsyndrome group. Stepwise multiple regression analyses showed that chronological age andmean mental age, collectively, accounted for 78% of the variability in vocabulary comprehensionand 80% of the variability in syntax comprehension in the Down syndrome group, with totalpasses on a hearing screening accounting for an additional 4% in each case Implications forresearch are discussed

KEY WORDS: Down syndrome, language disorders, comprehension, mental retardation,language development

Studies of children and adolescents with Down syndrome (DS) have frequentlyindicated problems in expressive language development greater than one mightexpect on the basis of cognitive delay in nonverbal domains or comprehension skill(Andrews & Andrews, 1977; Bray & Woolnough, 1988; Cardoso-Martins, Mervis, &Mervis, 1985; Cornwell, 1974; Dodd, 1975; Gibson, 1978; Greenwald & Leonard,1979; Harris, 1983; Hartley, 1986; Hill & McCune-Nicolich, 1981; Holdgrafer, 1981;Mahoney, Glover, & Finger, 1981; Miller, 1987, 1988; Mundy, Sigman, Kasari, &Yirmiya, 1988; Rogers, 1975; Rohr & Burr, 1978; Rosin, Swift, Bless, & Vetter, 1988;Smith & Tetzchner, 1986; Wiegel-Crump, 1981).

Much less consistent is any report of problems in language comprehension,although the frequent middle ear infections and hearing loss experienced by many ofthe children (Brooks, Wooley, & Kanjilal, 1972; Dahle & McCollister, 1986) might leadone to expect consequent delays in language comprehension. Among mentallyretarded children In general, specific deficits in comprehension, over and abovecognitive delay in nonverbal problem-solving domains, are encountered frequent-ly-in 25% (Miller, Chapman, & Bedrosian, 1978) to 60% (Abbeduto, Furman, &Davies, 1989) of the sample.

For children with Down syndrome, few studies of language comprehension relativeto nonverbal cognitive level exist, and the findings are inconsistent. Hartley (1982)finds poorer performance on syntactic comprehension tasks in children with Downsyndrome than in children with mental retardation of other origin, matched onvocabulary comprehension. Within the Down syndrome group, poorer performance is

© 1991, American Speech-Language-Hearing Association 1106 002 2-4685/91/3405-1106$0 1.00/0

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Chapman et al.: Language Comprehension in Down Syndrome 1107

associated with a left ear advantage (and presumably righthemisphere processing) (Hartley, 1985).

In contrast, Bridges and Smith (1984) report similar sen-tence interpretation strategies in children with Down syn-drome matched for verbal comprehension on the ReynellDevelopmental Language Scale (Reynell, 1969) to controls.Carr (1988) reports no differences on verbal vs. expressiveportions of the Reynell Test of Language Comprehension.

Rosin, Swift, Bless, and Vetter (1988) have demonstratedboth strengths and weaknesses in the comprehension skillsof adolescent boys with Down syndrome. Communicationprofiles showed single-word vocabulary comprehension, asindexed by the revised Peabody Picture Vocabulary Test(Dunn & Dunn, 1981), to be as good as that of controlsmatched for mental age on the Columbia Test of MentalMaturities. Syntactic comprehension in children with Downsyndrome, in contrast, was significantly worse than mentalage matched controls or a group who were retarded forreasons other than Down syndrome. Normal hearing was arequirement for participation in the Rosen et al. study; theauthors propose that the syntactic deficit is part of a generaldeficit in sequential processing.

Other explanations for comprehension deficits could in-clude hearing loss (Wilson, Folsom, & Widen, 1983); earlyotitis media (Whiteman, Simpson, & Compton, 1986); lack ofearly spoken language intervention programs or less thanoptimal mother-child interaction, sometimes mediated bymedical problems or periods of hospitalization; or failure tomatch samples on socioeconomic status, a variable known tobe associated with language skill in the normal population.

Researchers finding accelerated vocabulary comprehen-sion in DS children, as opposed to controls, have cited assources of stimulation vocabulary enrichment or early lan-guage intervention programs or the access to a wider varietyof language learning environments that is afforded the chro-nologically older DS children in vocational education.

Variations in subject selection and control group matchingprocedures complicate the interpretation of these studies.Some researchers have excluded the very subjects whoothers argue should be the ones to have comprehensiondeficits. For example, those with hearing loss have beenexcluded; or those with histories of hospitalization have beenexcluded, although such periods may contribute to impover-ished input or disruptions in mother-child attachment andinteraction (Miller, 1988). Ages of children studied havevaried; and there is some suggestion that both language andcognitive impairments may increase with age. (Or, alterna-tively, that measurement instruments are more sensitive atthe higher levels of functioning.) Some studies have ex-cluded children with low intelligibility.

The choice of comparison groups also offers problems.Matches on expressive language are clearly inappropriategiven the evidence that some DS children are expressivelydelayed. Matches on nonverbal cognitive level are compli-cated by tests that call themselves nonverbal (in responserequirements) but place demands on language comprehen-sion. Further, children with Down syndrome have beendescribed as having short-term memory deficits in cognitiveprocessing (although control groups in these studies, de-scribed as matched on mental age, have actually been

matched on comprehension vocabulary). Many of the non-verbal tests used in nonverbal mental age matching (e.g., theLeiter, the Columbia) do not make many short-term memorydemands. As syntactic comprehension tasks make suchdemands, it would seem appropriate to choose a controlgroup on the basis of nonverbal cognitive tests that includedsome short-term memory tasks.

This study investigates the variation in receptive vocabu-lary and syntactic comprehension in a sample of children andadolescents with Down syndrome aged 5-20 years, forwhom the only exclusionary criteria were moderate hearingloss or use of signing as the primary means of communicai-ton. Thus the sample should include individuals with mildhearing loss, histories of medical complications, or intelligi-bility problems that have been argued as possible correlatesof comprehension deficit.

A group of normally developing children was selected ascontrol subjects on the basis of combined performance onone nonverbal cognitive test that included short-term mem-ory demands and another that did not, from the same testbattery (Stanford-Binet, 4th ed., Bead Memory and PatternAnalysis subtests, Thorndike, Hagen, & Sattler, 1986); bothtests involved abstracted pattern matching rather than de-pending on school-taught content (another problem in choos-ing cognitive matching procedures when individuals havedifferent educational histories). The control group was alsomatched for socioeconomic status; the statewide recruitmentof DS children (and possibly the demographics of the oldercohort that their parents are drawn from) yielded a samplelower in years of education than the city alone would be likelyto yield, so recruitment of control children was extended torural areas.

We asked two questions: (a) whether children with Downsyndrome differed from a control group matched for meannonverbal cognitive level in their language comprehensionskills; and (b) how well variation in comprehension skill withineach group could be predicted on the basis of multipleregression analyses of the best predictors from each of sixareas: chronological age, sex, cognitive level, socioeconomicstatus, hearing status and history, and educational history.

Method

Subjects

Participating in the study were 48 children and adolescentswith Down syndrome, ages 5:6 (years:months) to 20:6, and48 children ages 2:0 to 6:0 who were developing normally(these are the same children described in Chapman, Kay-Raining Bird, and Schwartz, 1990). The control group meanwas matched to the Down syndrome group on nonverbalmental age, as determined by mean age-equivalent score onthe Bead Memory and Pattern Analysis subtests of theStanford-Binet, 4th ed. The groups were also matched onmothers' years of education. Table 1 summarizes the groups'mean chronological age, nonverbal mental age, mothers'years of education, and sex.

The children with Down syndrome were recruited fromWisconsin and northern Illinois through parent groups, per-

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1108 Journal of Speech and Heanng Research

TABLE 1. Children participating in study: Characteristics by group.

Group

Down syndrome(N = 48) Controls (N = 48)

Characteristic No. M SD No. M SD p*

Boys 30 23Chronological age (years) 12.54 4.50 4.16 1 16 <.05*Nonverbal mental age (years)a 4.58 1.45 4.71 1.43 NSMothers' education (years) 13.33 1.87 13.88 2.27 NSaBased on mean of Bead Memory and Pattern Analysis subtests of Stanford-Binet, 4th ed.*p < .05, t test of group difference

sonal referrals, and the Down Syndrome DevelopmentalMonitoring Program at the Waisman Center. All children whoused speech as their primary means of communication andwhose hearing showed no more than a mild loss wereincluded in the study, up to a limit of 13 subjects in each ofthe 4-year age ranges between 5 1/2 and 20 1/2 years.

Children were excluded if sign language was the primarymeans of communication or if they had a pure tone average forthe frequencies 500, 1000, and 2000 Hz greater than 45 dB inthe better ear. Five of the 53 Down syndrome children originallymeeting the criteria were excluded for reasons of meningitis,visual impairment due to nystagmus and cataracts, a geneticrecord indicating mosaicism, or a genetic record indicatingDown syndrome due to translocation (2).

Two of the older subjects did not have genetic records ofchromosomal analysis, although translocation in the parents'chromosomes had been ruled out. One of the subjectsincluded in the oldest group had an incomplete chromosome5 in addition to Trisomy 21 but fell within 1 standard deviationof the mean of his age group in this study in mental agemeasures.

The control subjects were recruited from children betweenthe chronological ages of 2 and 6 from Madison, WI, andsurrounding small communities. These ages correspondedto the main range of mental age scores in the children withDown syndrome.

Procedures

All children participated in a 3-hr protocol that included, inorder, a hearing screening, picture descriptions, story retell-ing, Form L of the Peabody Picture Vocabulary Test, Revised(PPVT-R), conversation and narration with the examiner, anobject hiding task (Chapman, Kay-Raining Bird, & Schwartz,1990), the Expressive Vocabulary, Bead Memory, and Pat-tern Analysis subtests of the Stanford-Binet, 4th ed., conver-sation and snack with a parent, a speech motor evaluation,delayed story recall, event narration, the Test for AuditoryComprehension of Language, Revised (TACL-R) (Carrow-Woolfolk, 1985), and the delay condition of the object hidingtask. Breaks were incorporated at frequent intervals. Parentinterviews elicited background data on hearing history, edu-cational and intervention history, and parent education andoccupation.

Hearing was screened using a portable Beltone audiome-ter in the experimental room. Pass/fail data were collected foreach ear at 25 and 45 dB HL (ANSI, 1969) for the frequen-cies 500, 1000, and 2000 Hz. Background data were col-lected through questionnaire, parent interview, and follow-uptelephone conversations.

Scoring

Comprehension. PPVT-R raw scores were converted toage-equivalent scores, in years. TACL-R subtest and totaltest raw scores were converted to age-equivalent ranges andthe midpoint of the range, in years, used as the age-equivalent score. The age-equivalent scores provided wereextrapolated to 27-29 months, for zero scores, from datanormed on children beginning at age 3; no child tested ineither group failed to pass some items on at least subtest 1and the total test.

Cognition. Raw scores on the Stanford-Binet 4th ed.Pattern Analysis and Bead Memory subtests were convertedto age-equivalent scores for each subject. A mean mentalage score was computed by averaging the two age-equiva-lent scores. In the case of two children in each group whopassed no item on the Bead Memory (below age 2:5 on thescale) but scored at least 2 years on the Pattern Analysis, ascore of 2 years was estimated for the Bead Memoryperformance to compute the mean mental age score. Adifference score was also computed by subtracting the BeadMemory age-equivalent score from the Pattern Analysisage-equivalent score.

A composite standard age score (SAS) was computed byconverting an individual's raw scores for Pattern Analysisand Bead Memory to standard age scores appropriate forabstract visual reasoning and short-term memory areas,respectively, using the tables appropriate to the individual'schronological age. These two scores were then added andtheir sum converted to a composite SAS score using theconversion table appropriate for the individual's chronologi-cal age. The composite SAS is designed to have a mean of100 and a standard deviation of 16.

Potential predictors of language comprehension werequantified from these data in three domains: socioeconomicstatus, hearing status, and educational history. These aredescribed in the following paragraphs.

34 1106-1120 Octoer 1991

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Chapman et al.: Language Comprehension in Down Syndrome 1109

Socioeconomic status. Three indices of socioeconomicstatus were computed: the number of years of mother'seducation; the number of years of father's education; and anoccupational index score (Stevens & Cho, 1985) for thefather's (or head of household's) job. This index converts anindividual's occupation into a score that reflects both theincome and the educational requirements of the job relativeto other positions in the work force. In the case of single-parent families, data on the other parent were also used. Inthe case of reconstituted families, the stepparent data wereused, and in the case of adopting families, the adoptiveparents' data.

Hearing status. Parents were asked whether their chil-dren had ever had tubes placed in either middle ear. Thesereports were scored for presence or absence (1 or 0) of tubesduring childhood. [We originally also asked parents to esti-mate the number of ear infections (otitis media episodes) thattheir child had experienced before his or her third birthday,but these could not be reliably reported.]

Two predictors were constructed from the hearing screen-ing data: the total number of passes achieved for both earsand the number of failures, plus 1, in the better ear. Given thesubject exclusion criteria, total passes varied from a possiblelow of 4 to maximum of 12 (2 ears x 2 intensities x 3frequencies). No subject failed any frequency at 45 dB in thebetter ear, so the index of failures in the better ear variedfrom 1 to 4.

Educational history: Down syndrome group. The par-ent reports of the child's educational history were quantifiedin two areas: preschool intervention programming and re-ceipt of speech-language therapy.

Intervention programming was quantified as the number ofyears, during the child's first 5 years, that he or she hadreceived intervention programming. Intervention periodswere defined as times containing a report of occupationaltherapy, physical therapy, special education, and/or speech-language services at least once per month.

Receipt of speech-language therapy was quantified bydividing the number of years the child had received speech-language therapy at least monthly by his or her age, yieldinga proportion score taking age differences into account.

Educational history: Control group. Educational histo-ries of the control group, aged 2-6 years, were quantifiedfrom the parental interviews to yield three potential predic-

tors: (a) the age at which the child began out-of-homedaycare, (b) the years of daycare in the home, and (c) theyears of preschool experience that the child had. Measures(b) and (c), of course, vary in part with the age of the child.

Results

Comprehension Testing

The means and standard deviations for performance ofeach group on comprehension measures are reported inTable 2, including vocabulary comprehension (PPVT-R age-equivalent scores), syntactic comprehension scores(TACL-R means of the age-equivalent ranges reported forthe three subtests and total test), and the difference betweenPPVT-R and TACL-R total score. The two groups did notdiffer significantly according to t tests (p > .05, two-tailed) oneither the vocabulary or the syntactic comprehension test,taken alone, nor on the syntactic comprehension subtests.They did differ significantly (p < .05), however, on thedifference between vocabulary and syntax comprehensionscore.

Within the Down syndrome group, the differences betweenvocabulary (PPVT-R) and syntax (TACL-R total) test scoreswas significant (p < .01, paired t test). Mean age-equivalentdifference was .94, almost a year better on vocabulary thansyntax. The difference was not significant within the controls(p > .05), averaging only .06 of a year.

The difference between vocabulary and syntax compre-hension increased significantly with age (p < .01) in both theDown syndrome group (r = .73) and the controls (r = .41, p< .01). Mean difference scores and their standard deviationsare shown by age ranges in Table 3 and displayed in Figure1. When the two oldest groups are compared by t test (n =13, each), adolescents with Down syndrome average signif-icantly better (p < .05) on vocabulary comprehension thancontrols (age-equivalent scores of 8.17 vs. 6.39) but show nodifference in syntactic comprehension (age-equivalentscores of 5.89 vs. 5.90, respectively). 'These two groups donot differ significantly in mean mental age or mothers' yearsof education.

The extent to which these group trends were true ofindividuals was examined by asking what percentage of

TABLE 2. Vocabulary and syntactic comprehension measures for children with Down syndromeand controls: Mean age-equivalent scores and standard deviations (n = 48, each group).

Down syndrome Control

Measure M SD M SD p

Vocabulary comprehensionPPVT-R 5.27 2.41 4.71 1.56 NS

Syntax comprehensionTACL-R total 4.33 1.41 4.65 1.28 NS

TACL-R I 4.81 1.79 5.16 1.54 NSTACL-R II 4.15 1.51 4.50 1.38 NSTACL-R III 4.31 1.75 4.62 1.64 NS

Difference, PPVT-R -TACL-R total .94 1.18 .06 .77 <.01

*p < .05, t test.

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1110 Journal of Speech and Hearing Research

TABLE 3. Mean difference, vocabulary (PPVT-R) - syntax (TACL-R total) age-equivalent score,by age groups.

Down syndrome (n = 48) Controls (n = 48)

Age range Age range(years) n M SD (years) n M SD

5.5-8.4 13 .04 .68 2.1-3.0 11 -.48 .328.5-12.4 11 .48 .58 3.1-4.0 11 .22 .79

12.5-16.4 11 .86 .91 4.1-5.0 13 -.07 .6316.5-20.4 13 2.23 1.01 5.1-6.1 13 .49 .90

individuals in each age range showed differences scores(PPVT-TACL) more than one standard deviation above orbelow the mean, using the control group's standard deviation(SD = .77) and mean (M = .06) as the reference. For thecontrol group, the percent of individuals falling below themean was 18%, 9%, 23%, and 15% for 2-, 3-, 4-, and 5-year-olds, respectively, or 16.7% overall. Control group individualsfell more than one standard deviation above their mean 0%,27%, 0%, and 38%, respectively, by age group, or 16.7%overall.

In contrast, individuals with Down syndrome never scoredmore than one (control group) standard deviation below the(control) mean difference score. Scoring more than onestandard deviation above the mean were 8%, 36%, 45%, and92% of the Down syndrome individuals in the 5-8, 8-12,12-16, and 16-20-year age ranges, respectively. Thus theproportion of individuals with Down syndrome who show avocabulary advantage relative to controls increases, withage, from almost none to almost all.

Overall, then, there appears to be evidence for an increas-ing advantage in vocabulary comprehension, compared tosyntactic comprehension, in adolescents with Down syn-drome, but little evidence for a difference in syntactic com-prehension compared to a group matched in nonverbalmental age and socioeconomic status.

The three TACL-R subtest scores are based on threedifferent kinds of content: TACL-R I, Word Classes & Rela-tions, taps vocabulary comprehension and semantic rela-tional comprehension conveyed by probable event knowl-edge. TACL-R II, Grammatical Morphemes, assessescomprehension of prepositions, noun inflections, verb inflec-tions, and derivational suffixes. TACL-R Ill, Elaborated Sen-tences, assesses comprehension of sentence modality(questions, negation), semantically reversible sentence con-structions (active and passive voice, direct/indirect objectconstructions), and complex sentence constructions in whichcomprehension may depend on a single word (e.g., themeaning of a conjunction) or extended constructional as-

DIFFERENCE OF PPVT - TACL SCORES

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AGE GROUPFIGURE 1. Mean difference between vocabulary (Peabody Picture Vocabulary Test-Revised)and syntax (Test of Auditory Comprehension of Language-Revised) age-equivalent scores asa function of age group in Down syndrome children (5-8, 8-12, 12-16, and 16-20 years) andcontrols (2, 3, 4, and 5 years). The vertical lines represent one standard deviation.

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34 110611201 October 1991

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Chapman et al.: Language Comprehension in Down Syndrome 1111

pects. Thus Subtest I can be said to require substantivevocabulary comprehension to a greater degree than II or III,and the latter two to require syntactic comprehension. In thecase of II, the listener must often process morphemes oflimited phonetic substance; in the case of III, the listenermust often remember and use word order as a cue tocomprehension. Thus the TACL-R subtests may be differen-tially sensitive to advanced or restricted vocabulary develop-ment (I), hearing impairment (II), and auditory short-termmemory or sequential processing deficits (III).

The three subtest scores were analyzed in a one-wayrepeated measures analysis of variance for each subjectgroup. For the Down syndrome group, a significant effect[F(2, 94) = 8.11, p < .01] of subtest was found, with SubtestI significantly different from II and III according to post hocScheffe test. Children and adolescents with Down syndromeperformed significantly better on the subtest tapping lexical,rather than syntactic, aspects of comprehension. For thecontrol group, a similar pattern of results emerged. A signif-icant effect [F(2, 94) = 8.98, p < .01] of subtest was found,with Subtest I significantly better than II or III in post hocScheffe test.

Predictors of Comprehension Performance

Predictor variables for language performance were con-structed in six domains for each group: chronological age,sex, nonverbal cognition, socioeconomic status, hearingstatus, and educational history. Means and standard devia-tions for the variables are listed in Table 4. The predictors aredefined and discussed in the following paragraphs.

TABLE 4. Means and standard deviations syndrome and controls (n = 48, each group).

Cognition. Cognitive predictors included mean mentalage, upon which the groups had been statistically matched;age-equivalent scores for the two Stanford-Binet subtestsupon which the mean had been based, Pattern Analysis andBead Memory; the difference between these; and the IQscore derived from these. Ttests of all but the last revealedsignificant group differences (p < .05) in Bead Memory, a testrequiring short-term memory for visually presented se-quences of differently shaped beads, with the group withDown syndrome performing more poorly. There was a cor-responding, but not significant, difference in the oppositedirection in Pattern Analysis scores. The mean difference ofthese two scores (Pattern Analysis - Bead Memory) wasalso significantly (p < .05) different between the two groups.The mean difference was larger for the Down syndromegroup than for the controls, for whom it was approximatelyzero, as standardization criteria would dictate.

For the Down syndrome group, the difference in cognitivesubtest scores increased significantly with age (r = .36, p <.01). Within age groups (see Table 5), paired ttests indicatedsignificant differences in magnitude of Pattern Analysis andBead Memory in every age range. The control group, incontrast, showed no significant correlation of the cognitivedifference score with age (r = -. 05, NS) and no significantdifferences between Pattern Analysis and Bead Memoryscore according to paired t test. Mean differences are illus-trated for the two groups, by age, in Figure 2.

The composite Standard Age Score (SAS) based on BeadMemory and Pattern Analysis is a deviation index withexpected mean of 100 and SD of 16. SAS decreasedsignificantly with age (r = -. 34, p < .05, n = 46) in the

of predictor variables for children with Down

Down syndrome Control

Variable M SD M SD JD

Chronological age (years) 12.54 4.50 4.16 1.16Cognition

Mean mental agea 4.58 1.45 4.71 1.43 NSPattern Analysis 5.26 1.98 4.69 1.53 NSBead Memory 4.04 1.21 4.72 1.52 <.05'Difference, Pattern - Bead 1.22 1.37 -0.03 1.03 <.01*Composite SASb 51.04 9.23 108.70 12.14

Socioeconomic statusMother's education (years) 13.33 1.87 13.87 2.26 NSFather's education (years) 13.29 2.38 14.00 2.47 NSOccupational prestige indexc 41.38 21.91 39.75 20.55 NS

Hearing statusTubes (1 = yes, 0 = no) .35 .48 .19 .39 <.05**Better ear (failures) 1.83 1.02 1.04 .20 <.01*Total passes, screening 9.29 2.53 11.69 .80 <.01

Educational historyProgram (years before 5) 3.76 1.06 - -Speech-language therapy

(proportion of life) .64 .21 -Age of out-of-home day care - - 1.96 1.70dYears of home day care - - 1.17 1.34 d

Years of preschool - - .72 .94 b

aBased on means of mental age-equivalent scores on Bead Memory and Pattern Analysis, nonverbalsubtests of Stanford-Binet (Bead Memory estimated at 2.0 for two untestable subjects in each group).bn = 46. cComputed according to Stevens and Cho (1985). dn = 47. en = 44.*Two-tailed t test. **One-tailed t test.

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1112 Journal of Speech and Hearing Research

TABLE 5. Mean difference, Pattern Analysisrange.

- Bead Memory age-equivalent scores, by age

Down syndrome (n = 48) Controls (n = 48)

Age range Age range(years) n M SD (years) n M SD

5.5-8.4 13 .64 1.24 2.1-3.0 11 -. 13 .698.5-12.4 11 .89 1.24 3.1-4.0 11 .35 .67

12.5-16.4 11 1.53 1.38 4.1-5.0 13 .03 1.1216.5-20.4 13 1.80 1.41 5.1-6.1 13 -.33 1.38

children with Down syndrome. These findings would beconsistent with a cumulative deficit in nonverbal cognitivefunctioning-one increasing with age-in Down syndrome.However, a negative correlation of SAS and age ap-proaches significance in the control group as well (r = -. 24,p < .06). Mean SAS values by age ranges are displayed inTable 6.

Thus, in the children with Down syndrome, there is evi-dence for an unusual pattern of nonverbal cognitive perfor-mance that increases in magnitude with age. The childrenwith Down syndrome performed relatively more poorly withincreasing age on a visual test that required short-termmemory for, and sequential production of, design sequencesthan on a test requiring analysis and re-creation of geometricvisual patterns.

Socioeconomic status. Three predictors of comprehen-sion status were constructed from socioeconomic indices:mother's years of education, a measure that correlates withlanguage development in young normally developing chil-

dren; father's years of education; and an occupational pres-tige index (Stevens & Cho, 1985) for the head of household.There were no significant (p > .05) differences between theDown syndrome and control groups on these measures.

Hearing status. One index of hearing status was whethertubes had ever been inserted in the ears. Two additionalindices were based on hearing screening at the time of test,which afforded 12 opportunities to pass (3 frequencies x 2sound levels x 2 ears): the number of failures in the betterear, and the total number of passes. All of these measuresdiffered significantly between groups (p < .05, one-tailed ttest).

Educational history. Measures of educational historywere constructed separately for the Down syndrome and thecontrol group because of the dissimilarity of their experience.For children and adolescents with Down syndrome, twopredictors were constructed: (a) the number of years, beforeage 5, that individuals had received intervention program-ming of some sort; and (b) the proportion of years of life that

DIFFERENCE OFPATTERN ANALYSIS - BEAD MEMORY

3.500

3.000

2.500c--< 2.000m 1.500I 1.000

z_ 0.500

0. 000< -0500

- 1.)00

-1. 500

DOWN SYNDROMEI CONTROL

j3 4

AGE GROUPFIGURE 2. Mean deference between Pattern Analysis and Bead Memory age-equivalent scoresas a function of age group In Down syndrome children (5-8, 8-12, 12-16, and 16-20 years) andcontrols (2, 3, 4, and 5 years). The vertical lines represent one standard deviation.

34 1106-11207 Octoer 1991

A-- v 411 I[

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Chapman et al.: Language Comprehension m Down Syndrome 1113

TABLE 6. Composite Standard Age Scores based on BeadMemory and Pattern Analysis subtests, by age range, forchildren with Down syndrome (n = 46).

Age range(years) n M SD Range

5.5-8.4 12 57.17 5.56 49-688.5-12.4 11 49.54 5.99 37-61

12.5-16.4 10 46.70 9.87 36-6516.5-20.4 13 50.00 11.47 36-74

individuals had received speech-language therapy specifi-cally.

For control children, measures were constructed reflectingthe child's age when out-of-home day care began, the yearsof home day care, and the years of preschool attendance.

Regression Analyses

Correlations of predictor variables in each of the sixdomains with the dependent variables of vocabulary compre-hension (PPVT-R age-equivalent score) and with syntaxcomprehension (TACL-R total score, mean of age-equivalentrange) are summarized in Table 7 for each group. Withineach domain, the best predictor (largest correlation, p < .10)was selected for entry into multiple regression equationsevaluating the predictor variables in a stepwise analysis.Children with Down syndrome and control children wereanalyzed separately.

Children with Down Syndrome

Selecting predictor variables. Mean mental age wasselected as the best cognitive predictor for each comprehen-sion analysis; the occupation prestige index was the bestsocioeconomic status indicator. Sex was never significantlyrelated to comprehension performance and was excludedfrom subsequent regression analyses.

The hearing history report of insertion of tubes variednegatively with chronological age (r = --.24, p < .06) as wellas comprehension, indicating a cohort or recency effect.Shifts in medical practice or strains of antibiotic-resistantbacteria may have contributed to this pattern. Total passes ofthe screening test was used instead as the hearing statuspredictor.

Among the educational history indices, only the number ofyears before age 5 that intervention programming had beenreceived was significantly (p < .05) related to either compre-hension measure, but the direction was negative rather thanpositive, indicating a cohort effect associated with changingpublic law and service program delivery. These variableswere excluded from further regression analyses.

Thus the four independent variables selected for entry intothe stepwise multiple regression equations were (a) chrono-logical age, (b) mean mental age, (c) occupational prestigeindex, and (d) total passes on hearing screening test.

Correlations among the four predictor variables selectedfor stepwise multiple regression analysis are shown, forchildren with Down syndrome, in Table 8. Stepwise multiple

TABLE 7. Correlations of predictor variables with vocabulary (PPVT-R) and syntactic compre-hension (TACL-R total) age-equivalent scores for children with Down syndrome and controls (n= 48, each group).

Down syndrome Control

Variable PPVT-R TACL-R PPVT-R TACL-R

Chronological age .80** .76** .88** .83**Sex -. 02 -.04 -.01 .12Cognition

Mean mental agea .77** .83'* .87** .88*Pattern Analysis .75** .82** .84** .7!)**Bead Memory .69** .72** .80** .87**Difference, Pattern - Bead .48** .56** .06 -.12Composite SASb .00 .13 .01 .14

Socioeconomic statusMother's education (years) .06 .01 .51* .3:3*Father's education (years) .09 .02 .27 ' .21tOccupational prestige index .25* .13 .29* .21t

Hearing statusTubes (1 = yes, 0 = no) -.11 -.16 .25* .33**Better ear (failures) -.15 -.12 -.09 -.16Total passes, screening .23t .24 t -.01 .03

Educational historyProgram (years before 5) -.59* -. 57* - --Speech-language therapy

(proportion of life) .04 .06 - --Age of out-of-home day care - - .28*b .27b

Years of home day care - -. 04 -.04b

Years of preschool - .70**d .59**d

aBased on means of mental age-equivalent scores on Bead Memory and Pattern Analysis, nonverbalsubtests of Stanford-Binet (Bead Memory estimated at 2.0 for two untestable subjects in each group).bn = 46. cComputed according to Stevens and Cho (1985). dn = 47. en = 44.*p < .01, one-tailed. **p < .05, one-tailed. tp < .10, one-tailed.

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1114 Journal of Speech and Heanng Research

TABLE 8. Intercorrelatlons among predictor variables for chil-dren with Down syndrome (n = 48).

Independent variable CA MA OPI

Chronological ageMean mental age .59**Occupational prestige index .16 .08Total passes, hearing screen -. 01 .07 .07Note. CA = chronological age; MA = mental age; OPI = occupa-tional prestige index..*p < .01.

regression was used with SPSS default settings for criteria inbuilding the regression equation: A variable was removed ata step if the probability of Fwas greater than or equal to .10and added at a step if the probability of F was the smallestand less than .05. Tolerance limits (the proportion of avariable's variance not accounted for by other independentvariables in the equation) and minimum tolerance (the small-est tolerance other variables had when an additional variablewas included) were less than or equal to .0001.

Vocabulary comprehension. Three variables accountedfor 82% of the variability in vocabulary comprehension in thegroup with Down syndrome: chronological age, mean mentalage, and total passes on the hearing screening test, with amultiple R of .91 and beta weights of .55, .44, and .21respectively. Age entered first, accounting for 64% of thevariance. Mental age entered second, accounting for anadditional 14%. Total passes entered third for an additional4%. A summary of the stepwise multiple regression analysisis given in Table 9.

Syntax comprehension. Three variables accounted for84% of the variability in syntactic comprehension as indexedby TACL-R total score: mean mental age, chronological age,and total passes on the hearing screening test, with amultiple R of .92 and beta weights of .56, .43, and .20respectively. Mental age entered first, accounting for 69% ofthe variance. Chronological age entered second, accountingfor an additional 11%. Total passes entered third, for anadditional 4%. A summary of the stepwise multiple regres-sion analysis is given in Table 10.

Syntactic subtests. The same four predictors--chrono-logical age, mean mental age, total hearing passes, and theoccupational prestige index-were entered in stepwise mul-tiple regression analyses with each of the three TACL-Rsubtests as dependent variables. Results are shown in Table11.

For Subtest I, chronological age, mean mental age, andtotal passes on the hearing screening all entered the equa-tion, in that order, accounting for 73% of the variance incomprehension score. Chronological age and mental age,

taken together, accounted for 69% of the variance. Hearingscreening contributed 4% more. Beta weights for the threevariables were .48, .44, and .19. This result is similar to thepattern found for vocabulary comprehension, in which chro-nological age is a better predictor than mental age, and isconsistent with the emphasis on lexical comprehension ofSubtest I.

In the analyses of Subtests II and III, the pattern of resultsis similar to that for the TACL-R total score: Mean mental ageenters the prediction equation before chronological age, andthe two together account for 62% and 67% of the variancerespectively, for Subtests II and IlI. Total passes on hearingscreening do not enter the equation for Subtest II scores,suggesting that mild hearing loss does not differentially affectthe comprehension of grammatical inflections. The betaweights for mean mental age and chronological age are .50and .38 respectively. Hearing passes account for an addi-tional 4% of the variance on Subtest III. Beta weights for thethree variables are .50, .40, and .21, respectively.

Cognitive subtest predictors. The effects of substitutingthe two cognitive subtests, Bead Memory and Pattern Anal-ysis, for mean mental age in the multiple regression analyseswere also examined for PPVT-R, TACL-R Total, and TACL-RSubtest scores, with the expectation that, to the extent thatmodality-independent short-term memory factors played arole in TACL-R total and TACL-R Subtest III performance,Bead Memory might contribute additionally to explainedvariance for those dependent variables. This was the casefor TACL-R total score but not Subtest III; Bead Memoryentered fourth in the equation, accounting for an additional1% of the variance (Pattern Analysis entered first, accountingfor 68% of the variance). In the other analyses, PatternAnalysis, the stronger predictor of the two in every case, wasthe only index of mental age to enter any of the equations,and in the same order as mean mental age in the originalanalyses.

Nor did multiple regression analyses of PPVT-R andTACL-R total scores carried out within each of the four agegroups, with the entry of age, Bead Memory and PatternAnalysis forced, show beta weights for Bead Memory'scontribution to increase with age, as might be expected if thegaps between cognitive subtests and comprehension testsboth arose from an increasing deficit in general short-termmemory. Beta weights are shown in Table 12.

Mental Age Controls

Selecting predictor variables. Table 7 summarized thecorrelations of predictor with comprehension variables for thechildren who served as controls. Mean mental age was the

TABLE 9. Predicting vocabulary comprehension In children with Down syndrome: Stepwisemultiple regression analysis.

Beta MultipleStep Predictor in R R2 F(eqn) Sig F

1 Chronological age .80 .80 .64 82.51 <.012 Mean mental age 46 .88 .78 80.68 <.013 Total passes, hearing screen .20 .91 .82 68.60 <.01

314 1106-1120 Octoer 1991

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Chapman et al.: Language Comprehension in D)own Syndrome 1115

TABLE 10. Predicting syntax comprehension (TACL-R total, age-equivalent score) In childrenwith Down syndrome: Stepwise multiple regression analysis.

Beta MultipleStep Predictor In R R2 F(eqn) Sig F

1 Mean mental age .83 .83 .69 100.85 <.012 Chronological age .42 .89 .80 89.90 <.013 Total passes, hearing screen .20 .92 .84 77.27 <.01

best of the cognitive predictors for both vocabulary andsyntax comprehension, just as it was in the group with Downsyndrome. Of the socioeconomic variables, mother's years ofeducation was the best predictor of comprehension, unlikethe group with Down syndrome but consistent with otherstudies of SES effects in normally developing children. Thepresence of tubes was the strongest correlate among thehearing status indicators. Of the educational history predic-tors, the number of years of preschool was the best predictor.Sex was not related to comprehension performance and wasexcluded from subsequent analysis.

Thus, the five predictor variables selected for entry into themultiple regression equations for controls were (a) chrono-logical age, (b) mean mental age, (c) mother's years ofeducation, (d) tubes, and (e) number of years of preschool.Their intercorrelations are summarized in Table 13 for thecontrol group.

Vocabulary comprehension. Results of the stepwisemultiple regression analysis of predictors of vocabulary com-prehension are shown in Table 14. Three of the five variablesentered the equation: chronological age, mother's education,and mean mental age, accounting for 90% of the variance inPPVT-R score. Beta weights for the three variables in theequation were .44, .24, and .43, respectively. Age enteredfirst, accounting for 78% of the variance. Mother's educationentered second, accounting for an additional 6%. Meanmental age entered third, accounting for an additional 6%.

Syntax comprehension. Results of the stepwise multipleregression analysis of predictors of syntax comprehension,as indexed by TACL-R total mean age-equivalent score, areshown in Table 15. Two of the five variables entered theequation: mean mental age and presence of tubes, account-ing for 81% of the variance in TACL-R total score. Betaweights for the two variables were .83 and .18, respectively.

Mean mental age entered first, accounting for 78% of thevariance. Presence of tubes accounted for an additional 3%.

Syntactic subtests. The same five predictors, chronolog-ical age, mean mental age, mother's years of education,tubes, and years of preschool, were evaluated in stepwisemultiple regression analysis with each of the three TACL-Rsubtests as dependent variables. Results are shown in Table16.

Discussion

Comprehension Skills in Children with DownSyndrome

In this study we found that children with Down syndromeshowed differences, increasing with age, between lexical andsyntactic comprehension skill. They also showed differences,increasing with age, between nonverbal cognitive subtests ofpattern analysis and short-term memory for bead arrange-ments. The magnitude of these differences was significantlygreater than those in a control group of children aged 2-6matched for mean mental age and socioeconomic status.

Taken separately, the variations in lexical and syntacticcomprehension skill are well predicted by the three variablesof chronological age, mean mental age, and total passes onthe hearing screening exam in multiple regression analyses.In each case, chronological and mental age together accountfor about 78-80% of the variance; hearing status predicts anadditional 4%.

Among the mental age-matched controls, vocabularycomprehension is well predicted by chronological age, moth-er's years of education, and mean mental age, accountingtogether for 90% of the variance. These results underscore

TABLE 11. Predicting syntax comprehension in children with Down syndrome: Stepwisemultiple regression analyses for age-equivalent scores on TACL-R subtests.

Beta MultipleStep Predictor In R R2 Feqn) Sig F

Subtest I: Word Classes and Relations1 Chronological age .74 .74 .55 55.83 <.012 Mean mental age .46 .83 .69 50.04 <.013 Total passes, hearing screen .19 .85 .73 38.81 <.01

Subtest II: Grammatical Morphemes1 Mean mental age .73 .73 .53 51.31 <.012 Chronological age .38 .79 .62 36.84 <.01

Subtest lii: Elaborated Sentences1 Mean mental age .76 .76 .57 61.42 <.012 Chronological age .39 .82 .67 45.70 <.013 Total passes, hearing screen .21 .84 .71 36.54 <.01

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1116 Journal of Speech and Heanng Research

TABLE 12. Beta weights by age group for children and adolescents with Down syndrome:Multiple regression analysis predicting vocabulary and syntax comprehension with age, BeadMemory, and Pattern Analysis.

Age group (years)

5.5-8.4 8.5-12.4 12.5-16.4 16.5-20.4Variable (n = 13) (n = 11) (n = 11) (n = 13)

PPVT-RAge .09 .02 .11 -.13Bead Memory .38 -. 35 .37 -.05Pattern Analysis .74 .44 .53 .79

TACL-RAge .03 .25 .11 -.10Bead Memory .40 -.22 .68 -. 06Pattern Analysis .64 .39 -. 06 .76

the importance of matching the control group in mean mentalage and mother's years of education to the Down syndromegroup. Syntactic comprehension is accounted for by meanmental age (78% of variance) and tubes, accounting for anadditional 3%.

Vocabulary Advantage or Syntactic Deficit forAdolescents with Down Syndrome?

How is the discrepancy between vocabulary and syntaxcomprehension, for adolescents with Down syndrome, to beunderstood? One possibility can be ruled out. The degree ofdiscrepancy is not related to nonverbal IQ (Standard AgeScore).

Are we seeing a deficit in syntactic comprehension, or aburst of new vocabulary learning, or both? Given the basis formental age matching used in this study, adolescents withDown syndrome can be described as having advancedvocabulary comprehension. That matching was based on theaverage of Pattern Analysis and Bead Memory age-equiva-lent scores, because language requires both simultaneousand sequential processing. If matching had been done on thebasis of nonverbal cognitive tasks that contained few require-ments for short-term memory or sequential processing, suchas Pattern Analysis alone, the subjects in this study mightalso have appeared to have mild deficits in syntax compre-hension. Had matching been done on the basis of PPVTscores, the subjects would have appeared to have deficits insyntactic comprehension and cognitive performances.

A vocabulary comprehension advantage could arise (a) ifintervention programs were heavily targeted toward vocabu-lary enrichment, compared to usual educational experience;or (b) if shifts in the learning environments of children withDown syndrome brought opportunities to learn vocabulary

usually not available to children of similar mental age lev-els-for example, vocational work settings; or (c) the in-creased opportunities for vocabulary learning, relative tomental age controls, make mental age-equivalent scoresoverestimations. In any case, the advantage ought to appearfor other children with mental retardation in similar interven-tion vocational programs, in contrast to mental age controls.No other control group of children with mental retardationwas included in this study, but Rosin et al. (1988) includedone and compared PPVT-R performance on standard scoresbased on mental age performance on the Columbia MentalMaturities Test; they found no evidence of vocabulary accel-eration in children with Down syndrome, children with mentalretardation, or mental age-matched children. Their resultssupport the interpretation that the difference in operational-izing mental age is the source of discrepant findings.

If the discrepancy is to be understood as a specific deficitin syntactic comprehension, one might argue that such adeficit could arise from (a) mild hearing loss, particularly inthe case of items testing morphological inflections of limitedphonetic substance, such as the nonsyllabic allomorphs ofplural, possessive, and present tense singular markings in

TABLE 13. Intercorrelations among predictor variables for con-trol group (n = 47).

Independent variable CA MA MEd Tubes

Chronological ageMean mental age .84*Mother's education (years) .35*' .29*Tubes (1 = yes, 0 = no) .42** .31* .09Years of preschool .68** .64** 58** .36**

Note: CA = chronological age, MA = mental age, MEd = mother'syears of education.*p < .05, one-tailed. **p < .01, one-tailed

TABLE 14. Predicting vocabulary comprehension (PPVT-R age-equivalent score) In controlchildren aged 2-6: Stepwise multiple regression analysis (n = 47).

Beta MultipleStep Predictor in R R2 F(eqn) Sig F

1 Chronological age .88 .88 .78 162.24 <.012 Mother's education .26 .92 .84 117.56 <.013 Mean mental age .43 .95 .90 126.18 <.01

34 1106-1120 October 1991

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TABLE 15. Predicting syntax comprehension (TACL-R total mean age-equivalent score) incontrol children aged 2-6: Stepwise multiple regression analysis (n = 47).

Beta MultipleStep Predictor In R R2 F/eqn) Sig F

1 Mean mental age .88 .88 .78 159.14 <.012 Tubes .18 .90 .81 92.86 <.01

English; or (b) general deficits in short-term memory peculiarto Down syndrome, such as might be tapped by the BeadMemory test of visual short-term memory; or (c) specificdeficits in auditory short-term memory, the kind of cognitivedeficit most frequently reported as typical of Down syndrome;or (d) deficiencies in short-term memory mediated by thearticulatory loop (Baddeley, 1986).

Although the regression analyses demonstrate that mildhearing loss accounts for some of the variance in bothvocabulary and syntactic comprehension score, the amountof variance (4%) is relatively small. Further, both theseresults and the failure of passes on hearing screening topredict variance on the TACL-R Subtest II of grammaticalmorphology suggest that the variance is not a factor thatcontributes differentially to perception of brief stretches of theacoustic input, with consequent, specifically syntactic, ef-fects.

If mild hearing loss were the principle explanation for asyntactic comprehension deficit, then we would expect it toaccount for more variance in syntax comprehension scoresthan in vocabulary comprehension scores, particularly foritems testing morphological inflections (Subtest II of theTACL-R); and we would expect Subtest II performance to bedepressed relative to the other subtests. None of thesepredictions is borne out in our data.

If short-term memory generally, including memory forvisual patterns, is implicated in a syntactic comprehensiondeficit, then TACL-R Subtest III, Elaborated Sentences,should show poorer performance than the other subtests forchildren with Down syndrome, but not controls. This is not thecase. In addition, the Bead Memory subtest should be abetter predictor than the Pattern Analysis of syntactic com-prehension, particularly of Subtest III. This was not the caseeither for total TACL-R score or Subtest III. Nor was it thecase that Bead Memory was a better predictor than PatternAnalysis when multiple regression analyses were undertaken

within each of the four age groups. Essentially, mean mentalage was always the best predictor, Pattern Analysis the bestin its absence. Thus the visual short-term memory or sequen-tial processing deficit noted in the performance of older Downsyndrome children on the Bead Memory subtest did notpredict variability in syntactic comprehension, although themagnitude and age course were similar.

If auditory short-term memory were implicated in thesyntactic comprehension deficit, we would also predict per-formance on the TACL-R Subtest III of elaborated sentenceconstruction to be worse than that on Subtest II. This was notthe case. The patterns of TACL-R subtest performance weresimilar to, and no different from, the patterns of performancein the control group. Further, the use of the picture pointingformat to test comprehension minimizes the contribution ofauditory memory factors in the assessment of syntacticcomprehension. However, it is still clear that matching sen-tence to picture may require relatively more short-term mem-ory for the sentence than does a single-word vocabulary test.No measures of auditory short-term memory were included inthe present protocol, so the relationship cannot be evaluateddirectly, although individuals with Down syndrome typicallyshow deficits on auditory-vocal tasks (Gibson, 1978;Pueschel, 1988).

A similar set of arguments can be made if a deficit inarticulatory rehearsal loop (Baddeley, 1986) is proposed asthe problem underlying poorer performance on syntacticcomprehension by children with Down syndrome. This pro-posal has the additional attraction that the use of the articu-latory loop may increase with age or developmental level,thus creating a deficit in older children's performance notfound in younger children. Presumably such a deficit shouldbe correlated with expressive language deficits.

The gradual emergence of an apparent syntactic compre-hension deficit, with age, could also be due in part to testcharacteristics. Prior to a developmental level of about 3

TABLE 16. Predicting syntax comprehension in children aged 2-6: Stepwise multiple regres-sion analyses for age-equivalent scores on TACL-R subtests.

Beta MultipleStep Predictor in R R2 RFeqn) Sig F

Subtest I1 Mean mental age .82 .82 .67 88.45 <.012 Chronological age .40 .85 .72 54.06 <.013 Mother's education (years) .19 .86 .74 41.02 <.01

Subtest I1 Chronological age .74 .74 .55 52.98 <.01

Subtest III1 Mean mental age .83 .83 .69 99.72 <.01

Note. Subtest I: Word Classes and Relations (n = 46); Subtest I: Grammatical Morphemes (n = 47);Subtest IIl: Elaborated Sentences (n = 46).

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1118 Journal of Speech and Heanng Research

years, syntactic content of tests typically manipulates thenumber of lexical items that the child must process, or simplyvocabulary content itself (e.g., Miller, Chapman, Branston, &Reichle, 1980), rather than word order or grammatical mor-pheme cues. Thus the degree to which syntactic comprehen-sion can be tested varies with developmental age in therange studied; the TACL-R itself is more heavily weighted byvocabulary content at the younger ages and on Subtest I,Word Classes and Relations. In addition, age-equivalentscores below 3 on the TACL are extrapolated linearly fromolder children's trends in performance, rather than from testdata. Finally, an increasing discrepancy in age-equivalentscores is expected, if acquisition rates are different for thetwo domains but constant.

Sources of Discrepant Nonverbal CognitiveAbilities in Down Syndrome

The search for a characteristic pattern of cognitive abilitiesin Down syndrome has produced conflicting accounts (Gib-son, 1978). Our finding that the subjects with Down syn-drome show increasingly discrepant performance with ageon the nonverbal Bead Memory and Pattern Analysissubtests of the Stanford Binet, 4th ed., is inconsistent withreports of their relative strengths on visuomotor tasks (Gib-son, 1978, ch. 7 & 8; Silverstein, Leguki, Friedman, &Takayama, 1982) but consistent with findings of sequentialprocessing deficits (Das, Kirby, & Jarman, 1979; Rosin et al.,1988; Snart, O'Grady, & Das, 1982) or visual storage deficits(McDade & Adler, 1980). However, sequential processing orshort-term memory deficits are more typically reported forauditory than visual memory in individuals with Down syn-drome (Ellis, Deacon, & Wooldridge, 1985, one third ofwhose subjects had Down syndrome; Marcell & Armstrong,1982; Marcell & Weeks, 1988; Pueschel, 1988; Varnhagen,Das, & Varnhagen, 1987). The deficits in auditory short-termmemory are not accounted for by requirements for verbalresponding (Marcell & Weeks, 1988) or by effects of atten-tional distractors (Marcell, Harvey, & Cothran, 1988).

It is also possible that relatively poorer performance on theBead Memory task arises from failures of verbal mediation-either a strategic failure to use rehearsal strategies, ordeficits in the articulatory loop working memory that has beenpostulated (Baddeley, 1986). If the last view is a correct one,we might expect that Bead Memory performance, in olderindividuals, was associated with degree of expressive syntaxdeficit; Chapman, Schwartz, and Kay-Raining Bird (in prep-aration) evaluate these predictions for language production.

Limitations of Study

Our own exclusion criteria constitute one limitation of thestudy: Children who depended on signing as their primarymeans of communication, and children who had more than amild hearing loss, were excluded from this study. Thus,comprehension deficits potentially present for signers, andprobably present for children with more than a mild hearingloss, are not included here. Our findings may overestimatethe level of comprehension skill in the population of children

and adolescents with Down syndrome (Trisomy 21) as awhole, then.

Relatively few children were excluded, however, by therequirement that speech be the primary means of communi-cation; fewer than might be excluded in younger cohorts ofchildren with Down syndrome, who frequently receive signinginstruction. Of the children and adolescents aged 5-20 in thisstudy, 65% had received signing instruction at one time, butonly 35% were currently using sign to support spokencommunication, and these were predominately younger chil-dren.

Our subject-finding methods worked through parent net-works; none of the children with Down syndrome recruitedwere living in institutions. A home-reared sample, however,may lead to cohort differences in a cross-sectional study,such as this one, that covers a 15-year time span. Institu-tionalization was a more common practice 15 years ago thannow. The fact that the older individuals participating in thestudy were also not institutionalized may mean that theirfamilies are unusual in other ways that are reflected inapparent correlations with age. Longitudinal follow-up of thesample will permit us to confirm age-related findings withinindividuals.

Secondly, the use of age-equivalent scores to determinelanguage delay relative to cognitive levels of functions has anumber of limitations [see, e.g., Lahey's (1990) recent dis-cussion], including the fact that difference scores do not havethe same significance at different ages. In particular, theapparent age gap in two abilities developing at differentconstant rates should increase with increasing age. The useof a control group design is thus an important adjunct to anyconclusions drawn from within-subject differences in scores.

Finally, the educational history measures reflected onlyquantity, rather than quality, of interactions (intervention,speech-language therapy, preschool experience) thought tofacilitate language development. Thus the failure of thesemeasures to contribute to the multiple regression analysesmay reflect our failure to measure qualitative aspects ofthese events.

Implications for Research

These findings help explain the disparate reports in theresearch literature. The age of children with Down syndromestudied, in particular, will affect the probability of finding asignificant difference from mental age-matched controls. Theway in which mental age matching is accomplished, inaddition, will increasingly affect the outcome as older childrenare tested. Matching on the basis of nonverbal tests withminimal short-term memory requirements, such as the Leiteror the Columbia, may put older children with Down syndromeat an effective disadvantage, relative to controls, on short-term memory tasks.

Similarly, the evidence for short-term memory deficits inDown syndrome is less clear than it appears to be becausethe "cognitive" matching in most of the memory studies hasbeen done on the basis of PPVT scores (e.g., Marcell,Harvey, & Cothran, 1988; Marcell & Weeks, 1988)-that is,on vocabulary comprehension, a procedure likely to put older

34 1106-1120 ctober 991

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Chapman et al.: Language Comprehension in Down Syndrome 1119

groups of Down syndrome at a disadvantage with respect tononverbal mental age if vocabulary age is actually acceler-ated, relative to other developmental dimensions, by accessto more varied life events.

Finally, the matching achieved on a comprehension mea-sure will depend on the relative amount of vocabulary andsyntactic comprehension tapped by the test. Bridges andSmith (1984), for example, found a slight delay (6-12months) in the interpretation strategies for active and passivesentences that children with Down syndrome aged 4-17years used, compared to children without retardationmatched on the basis of verbal comprehension scores on theReynell Developmental Language Scale. The Reynell hasboth vocabulary comprehension and syntactic comprehen-sion items. If it had been entirely a vocabulary test, Bridgesand Smith might have found larger delays; if items had beenchiefly syntactic, performance might have been comparable.

Hearing status was significantly related to comprehensionperformance in this study, confirming that the inclusion-orexclusion--of children with mild hearing loss would affectresults. However, the magnitude of comprehension effectsassociated with this index of current hearing level is muchsmaller than those related to chronological or mental age.

Acknowledgments

This research was supported by NIH Grant R01 HD23353 to theauthor Chapman and by Core Support Grant No. 5 P30 HD03352 tothe Waisman Center on Mental Retardation and Human Develop-ment. The help of the children and parents who participated isgratefully acknowledged, as is the assistance of the Down SyndromeDevelopmental Monitoring Program, directed by Joan Burns and JonMiller, in finding children, and that of Hye-Kyeung Seung in theliterature review. We thank Len Abbeduto for helpful comments. Apreliminary version of this paper was presented at the AnnualConvention of the American Speech-Language-Hearing Association,Boston, MA, November 18, 1988.

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Received August 13, 1990Accepted December 12, 1990

Requests for reprints should be sent to Robin S. Chapman, PhD,Department of Communicative Disorders, University of Wisconsin-Madison, 1975 Willow Drive, Madison, WI 53706.

34 1106-1120 Octoer 1991

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