JCPSLP Vol 15 No 2 2013_lores

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JCPSLP Volume 15, Number 2 2013 91
Language Transcripts (SALT; Miller, Gillon, & Westerveld,
2012), Computerized Language Analysis (CLAN;
MacWhinney & Snow, 1985), and Parrot Easy Language
Sample Analysis . Differences
between programs relate to the usability of the software,
availability of customer support, and fee for use.
After entering a transcribed and coded transcript, the
software programs automatically and accurately generate
multiple measures to describe children’s language skills,
including measures of linguistic form (e.g., mean length of
utterance, use of obligatory morphemes), content (e.g.,
number of different words), and use (e.g., percentage of
words in mazes). Software programs typically summarise
children’s language sample measures in a chart that
can be inserted into a clinical report and archived in the
child’s file (see Table 1 for an example). Each software
program has unique features that facilitate interpretation
of the language sample data. With the SALT software,
for example, SLPs have the opportunity to compare
their client’s performance with typical speakers in one of
the multiple databases. Clinicians can customise their
comparisons based on the type of sample collected
(e.g., conversation, narrative retells), population (e.g.,
mainstream Americans or mainstream New Zealanders),
and length of the sample. While there is not a database
specific to Australian speakers, Westerveld and Heilmann
(2012) documented that measures from American and
New Zealand samples were not significantly different; we
expect that there would also be minimal differences when
comparing those databases to samples from mainstream
monolingual Australian children. Measures from the
child’s sample can then be compared to the normative
comparison group and tracked over time. Table 1 shows an
example with a 7-year-old child with a language impairment
who completed two separate narrative retells. In the first
columns (Time 1), it is evident that most aspects of the
child’s productive language were in the low-normal range
compared to his age-matched peers. His lowest scores
were associated with word-level and utterance-level errors.
Further examination of the language sample revealed that
he had significant difficulty with pronouns, past tense,
and prepositions, which were addressed in an intensive
intervention. The Time 2 columns summarise measures
from a second narrative retell that was collected three
months later. After the intervention, a marked reduction was
observed in both word-level and utterance-level errors.
Table 1. Performance of a child with language impairment pre- and post-intervention compared to a
database of speakers with typical language development
Time 1 Time 2
Current age: 7;0 Current age: 7;3
Database: NZ Retell Database: NZ Retell
87 database participants 60 database participants
Time 1 Time 2
Transcript length Score ± SD Score ± SD
Total utterances 10 –0.92 12 –0.78
Total words 97 –0.36 98 –0.5
Elapsed time 1.77 0.15 2.20 0.61
Syntax/morphology
MLU in words 7.70 0.83 7.17 0.42
MLU in morphemes 8.00 0.66 7.33 0.10
Semantics
Number different words 44 –0.58 49 –0.48
Number total words 77 –0.61 86 –0.56
Mazes & abandoned utterances
Number maze words 21 0.85 13 0.11
% maze words 21%* 1.55 13% 0.55
Verbal fluency & rate
Words/minute 54.91 –0.74 44.55* –1.12
Within-utterance pauses 3** 4.57 2** 3.59
Between-utterance pauses 1 0.35 0 –0.55
Omissions & error codes
Omitted words 0 –0.36 0 –0.30
Omitted bound morphemes 0 –0.15 0 –0.18
Word-level errors 6** 3.82 2 0.68
Utterance-level errors 3** 5.01 1* 1.67
* 1 SD below age-matched peers
** 2 SD below/above age-matched peers
Note: Time 1 summarises baseline performance and Time 2 summarises data after an intensive intervention. “Score” columns summarise
children’s performance and “± SD” represent the difference (in standard deviations) between the child and mean scores of children in the
database. NZ retell was elicited using the Westerveld and Gillon language sampling protocol
rehabilitation-sciences/staff/dr-marleen-westerveld/language-sampling-and-other-resources).