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JCPSLP
Volume 18, Number 1 2016
Journal of Clinical Practice in Speech-Language Pathology
participants’ scores on the rhyme awareness subtest of
the PIPA compared with the other subtests (Wilks’ Lamda
= .686, F(4, 26) = 2.98, p = .038, multivariate partial eta
squared = .314), indicating that, on average, children with
CL/P in this study presented with poorer phonological
awareness skills in rhyme awareness.
The mean language score for this sample, based on the
CELF-P2 or CELF-4 assessment, was 94.50 (SD = 13.84;
range = 61–118), indicating that, on average, children with
CL/P in this study presented with language skills within
the average range. Participants’ language scores were
highly variable however, with 8 children (27%) in the study
presenting with a standard scores below 85.
This study also aimed to investigate the nature of the
relationship between phonological awareness abilities in
5-year-old children with CL/P and language skills, speech
production, middle ear function, and velopharyngeal
function. Table 3 illustrates correlations, and associated
levels of significance, between the dependent variable,
phonological awareness, and each independent variable.
A marginally significant correlation was detected between
phonological awareness scores and language scores (R
2
= .355, p = .054). Paired t-tests revealed no statistically
significant association between phonological awareness
and speech diagnosis (.060, p = .754), velopharyngeal
function (.028, p = .883), and middle ear function (–.044, p
= .817). Further, no statistically significant association was
detected between phonological awareness scores and
gender (–.124, p = .514), and cleft type (.167, p = .377).
Given no statistically significant correlation between
phonological awareness and speech diagnosis,
velopharyngeal function, and middle ear function was
detected, these four variables were omitted from the
final regression model. Table 4 displays the results of the
final univariate regression. A histogram of the residuals
closely approximated a normal distribution, validating
the assumption of normality for error in the model. The
final model accounted for 12.6% (p = .054) of variance in
phonological awareness scores. Language Score (.328,
p = .054) had a marginally significant relationship with
phonological awareness skills, indicating that language
abilities may influence the phonological awareness skills of
children with CL/P.
Discussion
The aims of this exploratory study were to explore
phonological awareness skills in 5-year-old children with
conducted using paired t-tests (for continuous variables)
and Pearson correlations (for ordinal variables) to determine
multicollinearity between the variables. The significance level
was set at
≤
.05. Bivariate analysis revealed no significant
relationships between phonological awareness and speech
production, velopharyngeal function, and middle ear
function. Univariate regression was then used to explore
the relationship between phonological awareness skills and
language performance. Regression analysis was used as a
statistical process for estimating the relationship between
phonological awareness and language performance. Model
significance was analysed using overall regression ANOVA.
Coefficient significance levels were set at
≤
.05.
Results
Table 1 displays a summary of speech diagnosis,
velopharyngeal function, and middle ear function of the 30
participants in the study. These assessment results suggest
that the majority of children with CL/P in this study
presented with adequate velopharyngeal function (n = 20;
66.7%), poor speech production skills (n = 24; 80%), and
abnormal middle ear function (n = 25; 73.3%).
The mean composite phonological awareness score for
this sample based on standard scores of the five subtests
of the PIPA was 44.50 (SD = 12.77; range = 25–71). Table
2 presents the descriptive statistics of each subtest of the
PIPA. According to test norms, mean standard scores
on each of the PIPA subtests were within the average
range (i.e., 7–13). However, participants’ scores were
highly variable. There was a significant difference between
Table 2. Participant’s standard scores on individual
subtests of the PIPA (N = 30)
PIPA subtest
M SD Range
Syllable Segmentation
9.23 3.059 3–15
Rhyme Awareness
7.43 3.014 3–13
Alliteration Awareness
9.23 3.081 4–15
Phoneme Isolation
9.40 4.123 6–16
Phoneme Segmentation
9.20 5.492 3–17
N.B.Standardscoresbetween7and13indicateskillswithinnormal
limits
Table 3. Summary of correlations between phonological awareness and candidate variables for regression
model (N = 30)
Variable
Language
score
Speech
diagnosis
Velopharyngeal
function
Middle ear
function
Gender
Cleft type
Correlation Phonologicalawareness
.335
.060
.028
–.044
–.124
.167
Significance
.054
.754
.883
.817
.514
.377
Table 4. Summary of final regression model (N = 30)
Model
Standardised co-efficients
t-value Significance 95.0% confidence interval for – Correlations
Beta
Lower bound Upperbound
Part
Constant
.869
.392
–18.360
45.392
Language score
.328
2.012
.054
–.006
.662
.355