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JCPSLP
Volume 15, Number 1 2013
Journal of Clinical Practice in Speech-Language Pathology
& Kresheck, 1983) and a spontaneous language sample
scored for grammatical complexity (see Procedures).
Language assessment results revealed that all
participants experienced grammatical deficits affecting
the accurate production of 3rd person singular present
progressive sentences containing a subject-verb-object
(e.g., The boy + is eating + a hot-dog
or
He + is eating
+ a hot-dog). Following consent to participate, 22 of
the 34 preschoolers were randomly selected to receive
intervention, leaving 12 participants to remain on the waitlist
for intervention. This selection allowed for equal numbers
in each intervention group and in the control group (see
Table 1). Half of the participants in intervention received
computer-assisted intervention (n = 11) and the other
half received table-top intervention (n = 11). Results of
Univariate ANOVAs revealed non significant between-group
differences for age (
p
= .126), gender (
p
= .902), nonverbal
IQ (
p
= .443), receptive language word-level (
p
= .087),
and receptive language sentence-level (
p
= .374), and
expressive grammar on the SPELT-P (
p
= .080) and DSS
(
p
= .127). There was no study attrition. Table 1 describes
participants’ demographic information.
Procedures
Assessment
Speech-language pathologists (SLPs) or graduate SLP
students evaluated participants’ language and cognitive
skills during a 90-minute individual assessment in a clinical
setting to determine participant suitability (pre-intervention).
This session included the collection of a 45-minute
spontaneous language sample during play (using a
standard procedure and including a dollhouse, toy
household objects and people and the
Spot Bakes a Cake
[Hill, 2003] and
Where’s Spot
[Hill, 2000] books). At least
100 intelligible utterances were collected and digitally
recorded from the participants at post-intervention and 3
months post-intervention, representing a break in
intervention (cf. Washington et al., 2011), to establish
spontaneous language outcomes associated with
intervention. Language samples were transcribed and
coded by assessors who were blind to group assignment
and assessment time points.
DSS procedures were used to analyse the language
samples (Lee, 1974). To obtain a DSS score, 50
consecutive utterances containing a subject and verb
were selected. Each utterance was scored for grammatical
accuracy (i.e., the DSS sentence point) and the eight DSS
The current study
The hypothesised link observed between grammatical
errors and processing constraints suggests that SLI has a
complex nature that necessitates grammatical language
interventions (Leonard et al., 2007). A secondary analysis of
the Washington et al. (2011) data was completed for the
DSS scored language samples to determine if expressive
grammar intervention facilitated accelerated growth (i.e., to
within normal limits), representing performance outside the
pre-test range for the spontaneous use of grammar skills
better than no intervention. Additionally, the authors tracked
decreases in per cent error rates for targeted grammatical
categories (e.g.,
personal pronoun
,
main verb
,
sentence
point
) for intervention and no intervention groups. The
following research questions were addressed:
1. Do computer-assisted and table-top intervention result
in accelerated growth in grammatical development
compared to no intervention?
2. Do computer-assisted and table-top intervention result
in significantly lower per cent error rates for targeted
grammatical categories compared to no intervention?
Method
Participants
Following ethical approval, 34, 3- to 4-year-olds (
M
= 4;4
months,
SD
= 5 months) who were randomly selected from
an intervention waitlist at a government-funded preschool
speech-and-language initiative in Ontario, Canada met the
Washington et al. (2011) study criteria (see below). Their
parents identified them as Caucasian (n = 32), Asian (n = 1),
or other (n = 1) and monolingual English speakers. The
sample included 27 boys and 7 girls, residing in urban and
rural regions.
All participants met the diagnostic criteria for SLI of
an expressive nature as outlined in the Washington et
al. (2011) study. These included normal hearing range,
normal receptive language and nonverbal cognition, i.e.,
one standard deviation from the mean on the Peabody
Picture Vocabulary Test-IIIB (PPVT-IIIB; Dunn & Dunn,
1997); the receptive portion of the Clinical Evaluation of
Language Fundamentals-Preschool (CELF-P; Wiig, Secord,
& Semel, 1992); and the Kaufman Brief Intelligence Test –
2: Matrices Subtest (KBIT-2; Kaufman & Kaufman, 2004).
For expressive grammar, children demonstrated skills at or
below the 10th percentile, on the Structured Photographic
Expressive Language Test-Preschool (SPELT-P; Werner
Table 1. Preschoolers’ pre-test characteristics
Total sample
Computer-assisted
Table-top
No intervention
(n = 34)
(n = 11)
(n = 11)
(n = 12)
Age-range
3;6 to 4;11
3;11 to 4;6
4;2 to 4;10
3;6 to 4;11
Gender-distribution
Female = 7
Female = 3
Female = 3
Female = 1
Male = 27
Male = 8
Male = 8
Male = 11
Receptive-word (PPVT-IIIB)
101.85 (4.88)
103.64 (5.71)
102.73 (3.77)
99.42 (4.30)
Receptive-sentence (CELF-P)
101.21 (6.95)
103.36 (8.65)
100.36 (8.10)
99.75 (2.90)
Expressive -SPELT-P
*10.26 (3.97)
*10.09 (2.30)
*12.27 (3.38)
*8.58 (4.99)
Expressive-DSS
*4.84 (.82)
*4.81 (1.08)
*5.21 (.66)
*4.51 (.54)
Expressive-MLU
*5.26 (.76)
*5.17 (.73)
*5.62 (.75)
*5.01 (.70)
Nonverbal IQ (KBIT-2 matrices subtest)
109.15 (10.10)
112.27 (12.35)
108.45 (9.61)
106.92 (8.24)
*Raw score.
Note.
Means reported with standard deviations in parentheses. Standard scores are reported for all measures, except for expressive-language.
Receptive-word (PPVT-IIIB; Dunn & Dunn, 1997), receptive-sentence (CELF-P; Wiig, Secord, & Semel, 1992), expressive-SPELT-P (Werner &
Krescheck, 1983), expressive-DSS (Lee, 1974), expressive-MLU (Brown, 1973; Miller, 1981), nonverbal IQ (KBIT-2; Kaufman & Kaufman, 2004).