Automated Language Environment Analysis (LENA) in Understanding Language Profiles in
Young Children with Down Syndrome, Autism, and Typical Development
C.
1
Parikh ,
P.
1
Anand ,
J.O.
2,3
Edgin ,
& A. M.
1,3
Mastergeorge
Family Studies and Human Development1; Department of Psychology2, University of Arizona, Sonoran UCEDD3
Methods
Previous research suggests that early communication
skills develop from experiences of successful
interactions that occur in everyday contexts (Marder &
Cholmain, 2006). Although there is variability in
language proficiency at any given age, the impact of
early experiences on language development is
substantial (Weisleder & Fernald, 2013). For children
who face significant language deficits and delays, such
as children diagnosed with Down syndrome (DS) and
autism spectrum disorders (ASD), the home
environment may play an exceptionally important role
in determining language acquisition and developmental
trajectories (Haebig, McDuffie, & Weismer, 2013).
Although children with DS and ASD display
considerable individual variability, they are at an
increased risk of impaired functioning in expressive
language, poor speech intelligibility, and sociocommunicative skills (Tager-Flusberg et al., 2005;
Thiemann-Bourque et al., 2014). Past research has
highlighted that since fewer learning opportunities are
available for children with DS and ASD, it is important
to facilitate and foster the acquisition of language
development in infancy. With the diversity of skills
observed in these populations, it is imperative to
distinguish language profiles that exist within the
home (Marder & Cholmain, 2006; Naess et al., 2011).
The present study utilized automated language
environment analyses (LENA) in a naturalistic
setting to explore differences among toddlers with DS,
ASD, and typical development (TD):
• Parent vocalizations (AWC);
• Child vocalizations (CV);
• Conversational turns (CT)
DS
ASD
TD
N = 42
N=9
N = 25
CA = 24.05 –
64.24m
MA = 8 – 36m
CA = 24.13 –
50.21m
MA = 8 – 36m
CA = 26.10 –
58.70m
MA = 24 – 36m
Males = 28
Females = 14
Males = 8
Females = 1
• Diagnosis of DS and autism
was confirmed by karyotype
report and/or other medical
records.
• Non-invasive LENA digital
language processor (see
figure 1) collected 16
continuous hours of audio
recording.
• Algorithms by LENA identified
the frequency of words spoken
by the child.
• Conversational turn-taking
and parent utterances were
also examined.
Results
• Preliminary correlational analyses between the three
variables of AWC, CV, and CT showed significant
positive relations (p < .01) across the 3 groups.
• A one-way ANOVA with diagnosis (AWC, CV, and CT)
as the between-subjects factor suggested a significant
main effect of diagnosis on CV: F (2, 73) = 9.34, p <
0.01 and CT: F (2, 72) = 5.36, p < 0.01.
• No main effect of diagnosis was found for AWC: F (2,
73) = 1.30, p = 0.28.
The University of Arizona
Leadership Education in Neurodevelopmental Disabilities
Average Audio Input in the Home
14000
Males = 16
Females = 9
• A total of N = 76 toddlers;
52 males and 24 females.
Figure 1. A LENA digital language processor and a
child-sized vest
16000
12000
Frequency Counts
Background
• Post-hoc Tukey HSD tests revealed
significant differences in CV between DS &TD
(p < 0.01) and DS & Autism (p < 0.05).
• Post-hoc tests conducted on CT revealed
significant differences only between DS &TD
(p < 0.01).
10000
Down Syndrome
Autism
8000
Typical Development
6000
4000
2000
0
Parent Utterances
Child Vocalizations Conversational Turns
Conclusions and Implications
• Overall, the findings suggest that regardless of
diagnosis, CV and CT patterns between the
parent and child are important for language
development.
• Across the 3 groups, parental input dominates
the majority of the audio environment.
• For CV, individual differences are found across
all 3 groups, highlighting the need for
population-specific interventions.
• The use of the LENA may contribute to improved
measures of early expressive language as it
exists in a natural context.
• Implications for using this information in children’s
language environment and parental behaviors
may encourage opportunities for increased
engagement that facilitate early and positive
learning experiences for very young children.
Acknowledgements
The authors acknowledge the University of Arizona Down Syndrome Research
Group, the Frances McClelland Institute, the University of Arizona LEND, and
the Sonoran UCEDD for their contributions to this project. The funding for this
project came from the following: The LuMind Foundation and Research Down
syndrome.