Language learning in Down syndrome: The speech and language profile compared
to adolescents with cognitive impairment of unknown origin
Robin Chapman
Children and adolescents with Down syndrome show an emerging profile of speech
and language characteristics that is typical of the syndrome (Chapman & Hesketh, 2000; Chapman,
2003; Abbeduto & Chapman, 2005) and different from typically developing children matched for
nonverbal mental age, including expressive language deficits relative to comprehension that
are most severe for syntax, and, in adolescence, strengths in comprehension vocabulary, improvements
in expressive syntax, but losses in comprehension of syntax (Chapman, Hesketh & Kistler, 2002).
Here we compare 20 adolescents with Down syndrome to16 individuals with cognitive impairment
of unknown origin, statistically matched for age and nonverbal mental age, to show that the
age-related strengths in vocabulary comprehension are not limited to the Down syndrome phenotype,
but are limited to a certain type of vocabulary test: for both groups, performance on the Peabody
Picture Vocabulary Test-3 is significantly greater than performance on the vocabulary subtest
of the Test of Auditory Comprehension of Language-3, which does not differ from the syntax comprehension
subtests. Vocabulary size, but not conceptual level, is a strength for adolescents with cognitive
impairment. In contrast, deficits in auditory-verbal working memory, syntax and vocabulary comprehension,
and narration of picture-books without an opportunity to preview them are all specific to the
adolescent group with Down syndrome. The expressive language deficit disappears when a preview
opportunity and picture support is given.
Chapman RS. Language learning in Down syndrome: The speech and language profile compared
to adolescents with cognitive impairment of unknown origin. Down Syndrome Research and Practice. 2006;10(2);61-66.
doi:10.3104/reports.306
The developmental emergence of speech and language skills
Studies of children and adolescents with Down syndrome have identified a specific behavioural
phenotype marked by deficits in expressive language, especially in speech intelligibility, syntax,
and grammatical morphology, accompanied by deficits in phonological working memory and strengths
in vocabulary comprehension compared to nonverbal mental age (see
Miller, Leddy & Leavitt, 1999;
Chapman & Hesketh, 2000,
Chapman, 1999, 2003, and
Abbeduto & Chapman, 2005, for reviews). The
expressive language and working memory deficits are more marked than comprehension skills, nonverbal
visual problem solving skills, daily living, or social skills (Dykens, Hodapp & Evans, 1994).
In adolescence, additional divergence in skill levels has been found, including actual losses
in longitudinal development of syntax comprehension, gains in longitudinal development of complex
syntax, and superior strength in vocabulary comprehension compared to nonverbal mental age matched
controls (Chapman & Hesketh, 2001,
Chapman, Seung, Schwartz & Kay-Raining Bird, 2000). The rate
of development of nonverbal visual short-term memory skills, in six years of longitudinal study,
is slower than nonverbal pattern analysis skills and predicts the rate of syntax comprehension
growth or loss in adolescence (Chapman, Hesketh & Kistler, 2002).
Vocabulary comprehension strengths emerge in adolescence, but whether this is unique to the
phenotype, or a product of increased life experience, is not clear.
Facon, Facon-Bollingier
and Gruber (2002) have reported that, for a group of 126 children and adolescents with mental
retardation, selected without regard to aetiology, chronological age explains a significant
(17%) amount of variance in PPVT-revised performance when entered after a nonverbal mental age
measure; but makes no additional contribution in predicting syntax comprehension, as measured
by the Test for the Reception of Grammar. Consistent with this view, Facon earlier reported
a significant correlation between chronological age and the age-equivalent score on the French
version of the PPVT for 29 children aged 6 to 13 years with Down syndrome (Facon, Gruber & Gardez,
1998) and for children and adolescents with mental retardation (Facon & Facon-Bollengier, 1997).
In our own work (Miolo, Chapman & Sindberg, 2005), the strength of adolescents' performance
on the PPVT has been replicated in a second study of individuals with Down syndrome (the group
included here), where it appears attributable to the nature of the test used. PPVT strengths
in performance were not replicated on a vocabulary test more nearly based on lexical selection
for conceptual difficulty (the Vocabulary subtest of the Test of Auditory Comprehension of Language-3);
in contrast, picturability and frequency of use governed selection of PPVT items. By this argument,
other adolescent groups with cognitive impairment of unknown origin should also show strengths
on the PPVT-3, but mental-age-commensurate performance on the vocabulary subtest of the TACL-3.
We test that prediction here, comparing the phenotype for Down syndrome in adolescence to a
group with cognitive disability of unknown origin matched statistically for chronological age
and nonverbal mental age, asking if the adolescent pattern of Down syndrome language and cognitive
skills more broadly characterises individuals with cognitive impairment, or is specific to Down
syndrome; and whether vocabulary performance varies with test.
|
Variable |
DS (n=20,
10 boys) |
CI (n=16,
7 boys) |
|
X |
(SD) |
X |
(SD) |
|
Chronological age |
15.79 |
(2.13) |
16.13 |
(2.11) |
|
Mothers' years of education |
15.35 |
(2.13) |
14.00 |
(2.53) |
|
Stanford Binet |
|
Pattern analysis age equivalent
|
5.07 |
(1.39) |
5.51 |
(2.19) |
|
Bead memory age equivalent
|
4.65 |
(1.19) |
5.23 |
(2.29) |
|
Kauffman-ABC Digit Span
age equivalent |
4.38 |
(1.68) |
5.67 |
(2.29) |
|
Nonword repetition test
(out of 96) |
55.75 |
(13.47) |
61.94 |
(24.45) |
|
Hearing status (0=failing at least one screening frequency; 1=passing all) * |
.50 |
(0.51) |
.80 |
(0.41) |
|
MLU (n=14, CI group)
|
|
Interview (C&I, yes-no &
pragmatic markers omitted, 9min.)
|
5.09 |
(1.57) |
5.56 |
(2.30) |
|
Narrative, relevant, C&I ave. |
6.35 |
(2.45) |
7.63 |
(3.00) |
|
previewed picture book
|
6.51 |
(2.78) |
7.40 |
(2.87) |
|
nonpreviewed picture book*
|
6.19 |
(2.39) |
7.85 |
(3.24) |
|
Vocabulary comprehension |
|
PPVT-3 age equivalent *
|
6.09 |
(1.76) |
8.10 |
(2.58) |
|
TACL-3 age equivalent *
|
5.16 |
(1.47) |
6.77 |
(1.83) |
|
Syntax comprehension |
|
TACL-3 grammatical morphemes age equivalent *
|
4.86 |
(1.16) |
6.47 |
(1.71) |
|
TACL-3 elaborated phrases age equivalent *
|
5.15 |
(1.23) |
6.34 |
(1.35) |
*groups differ significantly, p<.01, 2 tailed; 1-tailed
for hearing
Table 1 | Characteristics of participants with Down syndrome (DS) or cognitive impairment
of unknown origin (CI)
Method
Participants
We compared the language profiles of 20 adolescents with Down syndrome, aged 12 to 21, with
16 adolescents whose cognitive impairment was of unknown origin and whose visual nonverbal cognition
was statistically matched to the Down syndrome group (see
Table 1). The groups did not differ
significantly in chronological age or raw scores on the Bead Memory and Pattern Analysis subtests
of the Stanford Binet, 4th edition, the tests of nonverbal cognition. All participants
met the inclusionary criteria of a) monolingual use of spoken English at home and school; b)
mean length of utterance, from a narrative language sample, of at least 2.0 morphemes; c) pure-tone
average of less than 40dB in at least one ear; d) chronological age between 12 and 21 years;
and e) no history of severe behaviour, attention, or psychiatric disorder or developmental disorder
other than cognitive impairment, according to parental report.
Testing
In a three-hour protocol we administered a hearing screening (carried out by an audiologist)
at 20dB for 500, 1000, and 2000 Hz, and further testing to establish a pure tone average less
than 40dB for at least one ear if these were failed. Hearing status was scored 1 if the individual
passed all 20dB screening frequencies and 0 if they failed any. The protocol also included tests
of nonverbal cognition (the Bead Memory and Pattern Analysis subtests of the Stanford Binet-4th
ed., Thorndike, Hagen & Sattler, 1986), vocabulary comprehension (Peabody Picture Vocabulary
Test-3, Dunn & Dunn, 1997), and the vocabulary subtest of the Test of Auditory Comprehension
of Language-3 (Carrow-Woolfolk, 1999), syntax comprehension (grammatical morpheme and elaborated
phrase subtests of the TACL-3), interview language samples with the examiner on topics of school,
favourite activities, friends, and family; and narrative language samples derived from telling
stories to two different wordless picturebooks, one of which they had the counterbalanced opportunity
to preview. We also administered tests of auditory verbal working memory, including the Kaufman-ABC
number recall task (digit span; Kaufman & Kaufman, 1983) and the Nonword Repetition Test (Dollaghan
& Campbell, 1998); see Miolo, Chapman and Sindberg, 2005, for a more detailed account of these
procedures.
Transcription
Interview and narrative language samples were transcribed from audiotape using SALT conventions
for spelling and morpheme marking (Miller & Chapman, 1996) with the opportunity to listen at
least three times to the utterance; transcribers also had the picture books available. Transcriptions
were reviewed for reliability of morpheme transcription and utterance segmentation and retranscribed
if reliability did not reach 90% for each. The SALT program was used to compute measures of
mean length of utterance in morphemes (MLU) for the samples.
Results
Cognition
The group with cognitive impairment of unknown origin (CI) was selected to be statistically
similar to the group with Down syndrome in chronological age and the mean of the nonverbal visual
Stanford Binet subtests and did not differ significantly in those measures. Nor did the groups
differ significantly on the difference between their pattern analysis and bead memory subtests;
performance on pattern analysis was slightly better, by .42 (1.07) and .28 (3.25) years, for
the Down syndrome and cognitive impairment groups respectively, though the variability was significantly
greater in the CI group.
Working memory
With respect to phonological working memory measures, the groups did not differ significantly
on two measures, the total phonemes correct out of 96 on the Nonword Repetition Test or the
longest string recalled on the K-ABC digit span test. They did, however, differ significantly
(p<.05 1-tailed) on performance on 4-syllable words of the Nonword Repetition Test (Down
syndrome X=13.50, SD=6.31; cognitive impairment of unknown origin =18.00, SD=9.49) and on the
age-equivalent and age-based standard scores for the K-ABC Number Recall digit span test, with
a significantly (p<.05, 1-tailed) poorer performance in the group with Down syndrome
(for standard scores, X=63.00, SD=10.31), vs. the group with cognitive impairment of unknown
origin (for standard scores, X=73.67, SD=14.94); age-equivalent scores are reported in
Table
1. Thus the auditory-verbal working memory deficit that is found in Down syndrome appears to
be part of its specific phenotype, rather than a general feature of cognitive impairment.
Language comprehension and production
Multivariate tests, followed by univariate ones, evaluated group effects for comprehension (raw
scores on the PPVT-3, and the TACL-3 subtests for vocabulary, grammatical morphemes, and elaborated
phrases) and for production (mean length of utterance measures in morphemes for complete and
intelligible utterances in 9 minutes of interview and the two narrative samples from wordless
picture books, previewed or not, excluding yes-no answers and pragmatic acknowledgments in the
interview samples, and irrelevant utterances in the narrative).
All comprehension measures revealed significantly poorer performance in the group with Down
syndrome compared to the group with cognitive impairment of unknown origin (multivariate test
of group F(4, 30)=2.51, p<.05 1-tailed, partial eta-squared =.25) Univariate tests
are significant, p<.05, for TACL-vocabulary raw score (F(1,33)=5.90, partial eta-squared
=.152); for TACL-grammatical morphemes raw score (F(1,33)=10.03, partial eta-squared
=.23; for TACL-elaborated phrases raw score (F(1,33)=9.09, partial eta-squared =.22;
and for PPVT raw score (F(1,33)=6.46, partial-eta squared = .16). Thus the loss of comprehension
skills in adolescence appears specific to Down syndrome, and is poorer for both syntax comprehension
and vocabulary comprehension than the group with cognitive impairment of unknown origin.
Though production measures were lower in the group with Down syndrome, the overall multivariate
comparison was not significant, F(3, 30)=1.68, p=.10 1-tailed. The univariate
tests revealed that the non-previewed narrative was significantly shorter in mean utterance
length in the Down syndrome group, univariate F(1,32)=2.98, p<.05 1-tailed, with
a partial eta-squared of .09. The means (standard deviations) for DS were 6.19 (2.39) and for
CI were 7.85 (3.23), n=14 for the latter group. The effect of not having an opportunity to preview
the picture book is more limiting on MLU for adolescents with Down syndrome than for adolescents
with cognitive impairment of unknown origin, but with that opportunity, and with picture support
for a narrative sample that reveals more complex syntax, the expressive language deficit evident
in childhood years is not found here, in comparison to a group of adolescents whose cognitive
impairment is of unknown origin. These effects of language sampling procedures on measured MLU
are discussed further for the adolescents with Down syndrome by
Miles, Chapman and Sindberg
(2006).
Are vocabulary strengths greater on the PPVT than the TACL?
Within group paired t-tests evaluated the difference between PPVT-3 and TACL-3 Vocabulary age-equivalent
scores (see Table 1); these scores were significantly (p<.01) higher for the PPVT-3 in
each group, confirming that in both groups, vocabulary as sampled by the PPVT is greater than
expectations based on the TACL vocabulary test, or on mental age or syntax comprehension performance.
(Comparisons within groups of TACL-3 subscores vocabulary vs. morpheme comprehension or elaborated
phrases were not significant). When we examined the typically developing syntax-comprehension
control group (n=20) reported elsewhere (Miolo, Chapman & Sindberg, 2005), that group showed
no significant difference in TACL-3 and PPVT-3 age-equivalent scores, with means (SDs) of 5.32
(1.61) and 5.18 (1.61) respectively - as, indeed, one would expect with adequate norming of
the tests. Thus, the significantly better performance of the Down syndrome and cognitively impaired
groups on the PPVT-3, relative to syntax comprehension, is real, and appears attributable to
chronological age and the additional life experience it affords.
The role of hearing
A higher proportion of the group with Down syndrome failed at least one of the hearing screening
frequencies at 20 dB (50%, vs. 20%). To assess whether profile differences in comprehension
and production were attributable to hearing, group status, or both, we carried out hierarchical
regression analysis on the full group, adding hearing as the first level variable and group
membership (Down syndrome or intellectual impairment of unknown origin) as the second, for the
comprehension measures and the MLU measures.
Production
Hierarchical linear regression of hearing status, followed by group membership, for the MLU
variables revealed that hearing status only accounted for significant (p<.05) variation
in the MLU interview measure, Fchange(1,31)=5.006, p<.05, R-square=.14. There was no
additional effect of group. (Neither hearing nor group accounted for significant variance in
the MLU-average narrative measure).
Comprehension
For PPVT-3 raw score, hearing did not explain significant variance (Fchange(1,33)=1.188, p>.05); group, entered second, did (Fchange (1,32) = 5.509,
p<.05, R-square change=
.142. For TACL-vocabulary raw score, hearing explained significant variance (Fchange(1, 33)
= 4.380, p<.05), R-square =.12, and group explained additional significant variance(Fchange(1,
32) = 4.117, p<.05), R-square change=.10. Thus the TACL vocabulary subtest is more affected
by hearing status than the PPVT. For TACL-grammatical morphemes raw score, hearing explained
significant variance (Fchange(1,33) = 7.090, p<.05), R-square =.18, followed by group
membership (Fchange (1,32) = 6.217, p<.05), R-square change =.14. For TACL-elaborated
phrase raw score, hearing did not explain significant variance (Fchange(1,33) = 2.734, p>.05).
Group membership, entered second, did explain significant variance (Fchange(1,32) = 7.422),
p<.05, R-square change = .17).
In summary, hearing status accounted for differences in MLU-interview. Group membership accounted
for differences in comprehension performance on vocabulary tests, with hearing additionally
contributing to the TACL-vocabulary test but not the PPVT. Hearing and group membership accounted
for the differences in grammatical morpheme comprehension; group alone, for the poorer performance
on elaborated phrase comprehension by the adolescents with Down syndrome. Thus, the poorer comprehension
performance in the group with Down syndrome is attributable to the phenotype, with hearing status
(also arising from DS) contributing to TACL-vocabulary and grammatical morpheme comprehension
but not PPVT-vocabulary, nor TACL-elaborated phrase comprehension.
Predicting individual differences within groups
We further analysed predictors of individual difference in comprehension and production measures
within each group separately.
|
Measures |
Working Memory: |
Hearing |
|
K-ABC |
NRT |
|
|
TACL-vocab |
.39 |
.49* |
.37 |
|
TACL-gram morphemes |
.39 |
.21 |
.51* |
|
TACL-elab phrases |
.25 |
.58** |
.30 |
|
PPVT |
.32 |
.28 |
.18 |
|
MLU Narrative |
.57** |
.58** |
.18 |
|
MLU Interview |
.59** |
.54* |
.33 |
*p<.05 **p<.01
Table 2 | Down syndrome (n=20): Correlations between predictor
variables and comprehension and production measures
Down syndrome
Nonverbal cognition and visual working memory were not significantly correlated with any of
the comprehension or production measures, and were excluded from consideration. The correlations
of phonological working memory measures (K-ABC digit span, Non-word Repetition Test) and hearing
status with the language measures are shown in Table 2. Comprehension measures were significantly
related to the NRT, for TACL-vocabulary and elaborated phrases; and to hearing, for TACL-grammatical
morphemes. MLU in both narrative and interview samples was significantly predicted by the combination
of phonological working memory measures in regression analyses, with approximately equal contributions
by each measure. For MLU narrative, R-squared=.53, F(2,17) =9.50, p<.002; for
MLU interview, R-squared=.51, F(2, 17)=8.99, p<.002.
|
Measures |
Working Memory |
Nonverbal Cognition |
|
|
K-ABC |
NRT |
Bead |
Pattern |
|
TACL-vocab |
.50* a |
.23 |
.50* a |
.30 a |
|
TACL-gram morphemes |
.78** b |
.51* a |
.54* |
.51 a |
|
TACL-elab phrases |
.73** a |
.47 |
.49 |
.35 a |
|
PPVT |
.65** |
.35 |
.28 |
.51* |
|
MLU Narrative |
.60* c |
.57* b |
.41 |
.45 b |
|
MLU Interview |
.52 c |
.42 b |
.32 b |
.41 b |
a n=15 b n=14 c n=13 *p<.05 **p<.01,
2-tailed
Table 3 | Cognitive impairment of unknown origin (n=16): Correlations between predictor
variables and comprehension and production measures
Cognitive impairment of unknown origin
Nonverbal cognition (SB Pattern Analysis) and working memory (SB Bead memory; K-ABC digit span,
Non-word repetition test) measures were examined as predictors of individual difference in comprehension
and production measures within the group with cognitive impairment of unknown origin (see
Table
3). In this relatively small-n group, only K-ABC digit span contributed significant variance
in models predicting comprehension and narrative production performance; addition of other,
moderately correlated, predictors did not add significant additional explained variance.
Summary of predictors of individual variation
These foregoing analyses suggest that phonological working memory plays an important role in
comprehension and production performance by both groups; but that the Nonword Repetition Test,
with its greater component of long-term knowledge of phonotactics, is more important for the
Down syndrome group than the index of phonological store and rehearsal provided by the K-ABC
digit span in the CI group. Additionally, hearing status affects DS grammatical morpheme comprehension
and interview-MLU.
Phenotypic profiles
The significant differences between the groups (matched in nonverbal visual cognition) in auditory-verbal
working memory, comprehension measures, and the non-previewed narrative language sample confirm
a specific behavioural phenotype for language and cognition in adolescents with Down syndrome,
compared to individuals for whom the origin of cognitive impairment is unknown. Compared with
the adolescents with cognitive impairment of unknown origin, the adolescents with Down syndrome
show poorer auditory-verbal working memory skills, poorer comprehension skills, and more limited
narrative language skill when no opportunity to preview the story is provided. Both groups showed
strengths, relative to their nonverbal mental age performance, on vocabulary comprehension measured
by the PPVT (reflecting vocabulary size), but not on vocabulary comprehension on the TACL-vocabulary
subtest (reflecting, to a greater degree, conceptual level of vocabulary).
The profile for adolescents with Down syndrome differs from that reported for children with
Down syndrome in its age-associated strengths in vocabulary size (PPVT), deficits relative to
non-verbal age in syntax comprehension, and improved performance on narratives produced with
previewing and picture support.
Limitations of study
The group with cognitive impairment of unknown origin was smaller than we had hoped; it proved
difficult to find individuals for whom attention deficit disorder or other conditions (seizures,
psychiatric diagnoses) were not reported, and the origins of cognitive impairment have been
identified in many more individuals today than in the past. Indeed, the comparison group is
a moving target, as research sorts out genetic and environmental causes. Thus the predictors
for the CI group variation should be especially viewed with caution.
Acknowledgments
This research was supported by National Institutes of Health grant R01-HD-23353 to R. Chapman,
with additional support from the National Down Syndrome Society. Thanks to the parents and participants
who made the work possible, and to the many colleagues who participated in this research, including
Cynthia Bridge, Katharine Gigstead, Dr. Linda J. Hesketh, Dr. Sally Miles, Dr. Giuliana Miolo,
and Heidi Sindberg.
Correspondence
Robin Chapman • Waisman Center, 1500 Highland Ave., Madison, WI 53705 USA • chapman@waisman.wisc.edu
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