Discussion Week 4 Possible Effects of Poverty on Young Children’s

Discussion: Week 4: Possible Effects of Poverty on Young
Children’s Language and Literacy Development
Imagine that there are two 4-year-old girls standing in front of
you. One girl, whom you might assume to be from a more
economically affluent home, has hair that cascades down in neat
curls, a dress ablaze with bright colors, and a new princess
lunchbox in her hand. The other girl appears a bit unkempt, with
mismatched socks and a sweet, yet sleepy, smile. Without
hearing either girl speak, which might you select as the one
with a greater vocabulary? Why?
Like most people, you might gravitate toward the child who
appears to be from the more economically affluent home.
Although this choice might seem stereotypical, this selection
does mirror findings from research studies that have linked
vocabulary development and skill statistically with economic
background. For example, one study found that by 3 years of
age, there was a 30 million word gap between children from the
wealthiest and the poorest families (Fernald, Marchman, &
Weisleder, 2013). What is the reason for this gap? How can the
daily contrasts between each environment affect the ability to
acquire and develop language?
Simply put, language is derived largely from parental support
and diverse experiences. Because of a variety of factors,
children in low income environments generally do not have the
variety of experiences that those in higher income families
have, nor are they exposed to as rich a speaking and reading
vocabulary. Consider again the two children. How might their
mornings have been different? For example, if the first girl’s
mother spent time doing her daughter’s hair, how might she
have been talking to and supporting her daughter’s literacy at
the same time? And if the second girl put on her own socks,
what language opportunities might her mother have missed
while she was nervously gathering enough change for bus fare
and her daughter’s lunch? As the second mother worked to

provide, she might have felt she had less opportunity to engage
her daughter in child-directed speech, which is the case for
many children in low income environments.
In this Discussion, you explore the possible effects of poverty
on young children’s language and literacy development.
To prepare
Review the Roseberry-McKibbin (2012) article in the Learning
Resources and reflect on the statistics that highlight the effects
of poverty on early language experiences. Then, select one of
the following scenarios as the focus of your Discussion posting.
Select one of the following scenarios as the focus of your
Discussion posting.
Post the following: Describe the strategies you observed in your
selected scenario and explain whether they were effective and
appropriate for the child and family presented. Then, explain
what, if anything, you would do differently and why you think
your strategies might be more effective. Last, share any
assumptions you had about the effects of poverty on language
and literacy that were confirmed or dispelled.
Selected Scenarios
PBS: Frontline. (2017). Poor Kids. Retrieved June 19, 2018
from https://www.pbs.org/wgbh/frontline/film/poor-kids/
Barnardo’s. (n.d.-b). Tatiana’s story [Video file]. Retrieved
September 29, 2015, from
https://vimeo.com/groups/9196/videos/7141717
Fessler, P. (2014). One family’s story shows how the cycle of
poverty is hard to break [Blog post]. Retrieved from

http://www.npr.org/2014/05/07/309734339/one-familys-story-
shows-how-the-cycle-of-poverty-is-hard-to-break
Mann, R. (2013). Louisiana teachers share their stories of child
poverty: Robert Mann. The Times-Picayune. Retrieved from
http://www.nola.com/opinions/index.ssf/2013/08/louisiana_teac
hers_share_their.html
In Two 100 word response….
Share any additional assumptions that were confirmed or
dispelled by reviewing your colleagues’ postings
The following resources should be reviewed before you
participate in the Week 4 Discussion:
Carey, B. (2013). Language gap between rich and poor children
begins in infancy, Stanford psychologists find. Retrieved from
http://news.stanford.edu/news/2013/september/toddler-
language-gap-091213.html
Colker, L. J. (n.d.). The word gap: The early years make a
difference. Teaching Young Children, 7(3), 26–28.
Hart, B. & Risley, T. R. (2003). The early catastrophe: The 30
million word gap by age 3. Retrieved from
http://www.aft.org/ae/spring2003/hart_risley
Pungello, E. P., Iruka, I. U., Dotterer, A. M., Mills-Koonce, R.,
& Reznick, J. S. (2009). The effects of socioeconomic status,
race, and parenting on language development in early
childhood. Developmental Psychology, 45(2), 544–557.
Roseberry-McKibbin, C. (2012). The impact of poverty and

homelessness on children’s oral and literate language: Practical
implications for service delivery. Paper presented at ASHA
Schools Conference, Milwaukee, WI. Retrieved from
http://www.asha.org/uploadedFiles/Poverty-Homelessness-
Childrens-Oral-Literate-Language.pdf
26 TEACHING YOUNG CHILDREN VOL 7 NO 3
n e w s f r o m t h e f i e l d
Children’s vocabulary skills are linked
to their economic backgrounds. By 3
years of age, there is a 30 million word
gap between children from the wealthi-
est and poorest families. A recent
study shows that the vocabulary gap is
evident in toddlers. By 18 months, chil-
dren in different socio-economic groups
display dramatic differences in their
vocabularies. By 2 years, the disparity
in vocabulary development has grown
significantly (Fernald, Marchman, &
Weisleder 2013).
The study, conducted by researchers
at Stanford University, tested the lan-
guage processing of 18- and 24-month-
old toddlers using pictures, instructions,
and eye response. Each toddler sat in
her caregiver’s lap as images of two fa-
miliar objects were shown on a screen.
(The caregiver wore sunglasses so the
child could not be influenced by the

caregiver’s responses to the questions
or images.) A recorded voice identified
one of the objects by name and used
it in a sentence (Look at the doggy).
The Early Years
Make a Difference
Laura J. Colker
©
j
u
l
ia
l
u
c
k
e
n
b
il
l
TYC V7N3 16-32.indd 26 1/13/14 3:42 PM
FOR THE PRESCHOOL PROFESSIONAL NAEYC.ORG/TYC

27
Supporting Dual
language learnerS
Eliminating the word gap is an
important goal, especially when
working with children who are new
to English. There are two key strate-
gies to add to the suggestions in
this article. First, do as many of the
recommended activities as possible
in the children’s home languages.
This helps you assess their prior
knowledge and know that they un-
derstand what is going on around
them. Second, intentionally con-
nect new English words to words
they understand in their home
language to help them build their
English vocabulary. For example,
before you sing a song in English,
explain to children what the words
mean in their home language so
they understand what they’ll be
singing about.
The researchers filmed the child’s eye
movements, tracking which picture the
child looked at (vocabulary) and how
long this took in milliseconds (process-
ing time). (Watch a two-minute video
of the study at www.youtube.com/
watch?v=I7HN5LJOc-w&feature=

youtu.be.)
Children from higher economic
backgrounds looked at the identified
object faster and spent more time look-
ing at the correct image. At 24 months,
children from the lower economic
group were performing at the same
level as the 18-month-olds from the
high economic group in both speed and
accuracy. The study also focused on the
way children process new vocabulary.
Here, too, young children from homes
with low incomes lag behind children
of the same age who are growing up
in more affluent circumstances (Snow
2013).
This new information connects to
what researchers discovered earlier.
The landmark Hart and Risley study
in 1995 identified “remarkable differ-
ences” in the early vocabulary experi-
ences of young children. Researcher
and author Betty Hart described the
results of their observations: “Simply
in words heard, the average child on
welfare was having half as much expe-
rience per hour (616 words per hour) as
the average working-class child (1,251
words per hour) and less than one-third
that of the average child in a profes-
sional family (2,153 words per hour)”
(Hart & Risley 2003, 8). This is impor-
tant because vocabulary development
during the preschool years is related to

later reading skills and school success
in general.
What this means for you
Eliminating this inequality will
require early interventions that directly
address the problem. Preschool teach-
ers can build on what children already
know and respond to their interests
to introduce and reinforce new words.
Here are some things you can do to help
preschoolers build their vocabularies:
• Use new and interesting words in nat-
ural conversations. Try this at meal-
times or when presenting a new toy
or material. Introducing a new word
in context helps children learn what
it means. For example, it’s easier for
children to learn what a ukulele is
when they can see and hear it as well
as listening to you say the word.
• Use gestures and facial expressions
to help children make sense of new
words. For example, when introduc-
ing the word joyful, you might smile
and wave your arms about to convey
what it means.
©
j
u
l

ia
l
u
c
k
e
n
b
il
l
TYC V7N3 16-32.indd 27 1/13/14 3:42 PM
28 TEACHING YOUNG CHILDREN VOL 7 NO 3
Help families talk with their children more. Sign and make
copies of the
Message in a Backpack on page 29 to send home. It’s al so
available online
(in English and Spanish) at naeyc.org/tyc.
• Sing with children and recite poetry
and rhymes to playfully introduce
vocabulary.

• Talk with children and encourage
children to talk with one another.
Keep the conversation going by ask-
ing questions, making comments,
and inviting children to think and
share their ideas.
• Read to children daily, taking time
to go over new words. Look for books
with illustrations that provide clues to
word meanings.
• Think about new vocabulary words
that might come up on a field trip
as part of the experience. A trip to
an art exhibit could introduce the
word landscape, while a trip to a pizza
restaurant might introduce kneading
dough.
• Give children ample time to learn
the meaning and uses of new words
before moving onto other words.
• Help families understand how impor-
tant it is to talk with their children
and share new vocabulary words.
Send home suggested conversation
starters based on children’s inter-
ests and classroom projects. Include
discussion questions in family literacy
packs. Post videos of conversations
between teachers and children.
• Advocate for equity. Make sure that
all children have opportunities to

learn and understand the meaning
and uses of new words. TYC
reSourceS
too small to fail. Website. toosmall.org.
rich, M. 2013. “language-Gap study bolsters a
push for pre-k.” New York Times, october 21. www.
nytimes.com/2013/10/22/us/language-gap-study-
bolsters-a-push-for-pre-k.html.
White, r. 2013. “language Gap between rich and
poor evident in toddlers.” reporting on health,
children's health Matters, october 9. www.
reportingonhealth.org/2013/10/08/language-gap-
between-rich-and-poor-evident-toddlers.
referenceS
fernald, a., V.a. Marchman, & a. Weisleder.
2013. “ses Differences in language processing
skill and Vocabulary are evident at 18 Months.”
Developmental Science 16 (2): 234–48.
hart, b., & t.r. risley. 1995. Meaningful Differences
in the Everyday Experience of Young American
Children. baltimore: brookes.
hart, b., & t.r. risley. 2003. “the early
catastrophe: the 30 Million Word Gap by age 3.”
American Educator 27 (1): 4–9. www.aft.org/pdfs/
americaneducator/spring2003/theearlycatastrophe.
pdf.
snow, k. 2013. “new research on early Disparities:

focus on Vocabulary and language processing,”
naeyc (blog), october 29. www.naeyc.org/blogs/
gclarke/2013/10/new-research-early-disparities-focus-
vocabulary-and-language-processing.
©
n
a
e
y
c
TYC V7N3 16-32.indd 28 1/13/14 3:42 PM
Copyright of Teaching Young Children is the property of
National Association for the
Education of Young Children and its content may not be copied
or emailed to multiple sites or
posted to a listserv without the copyright holder's express
written permission. However, users
may print, download, or email articles for individual use.
The Effects of Socioeconomic Status, Race, and Parenting on
Language
Development in Early Childhood
Elizabeth P. Pungello, Iheoma U. Iruka, Aryn M. Dotterer,
Roger Mills-Koonce, and J. Steven Reznick
University of North Carolina at Chapel Hill

The authors examined the associations between socioeconomic
status (SES), race, maternal sensitivity,
and maternal negative-intrusive behaviors and language
development in a sample selected to reduce the
typical confound between race and SES (n � 146). Mother–
child interactions were observed at 12 and
24 months (coded by randomly assigned African American and
European American coders); language
abilities were assessed at 18, 24, 30, and 36 months. For
receptive language, race was associated with
ability level, and maternal sensitivity and negative-intrusive
parenting were related to rate of growth. For
expressive communication, race, SES, and maternal sensitivity
were associated with rate of growth; race
moderated the association between negative-intrusive parenting
and rate of growth such that the relation
was weaker for African American than for European American
children. The results highlight the
importance of sensitive parenting and suggest that the
association between negative-intrusive parenting
and language development may depend upon family context.
Future work is needed concerning the race
differences found, including examining associations with other
demographic factors and variations in
language input experienced by children, using culturally and
racially validated indices of language
development.
Keywords: socioeconomic status, race, parenting, language
development
Early language is associated with later academic achievement
(Craig, Connor, & Washington, 2003; Magnuson & Duncan,
2006;
National Institute of Child Health and Human Development

[NICHD] Early Child Care Research Network, 2005; O’Neill,
Pearce, & Pick, 2004; Scarborough, 2001; Stevenson &
Newman,
1986; Storch & Whitehurst, 2002). Thus, understanding the
factors
that are related to young children’s language development has
important implications for implementing early education
programs
aimed at enhancing school readiness and reducing the
achievement
gap in academic success that exists at present between African
American and European American children in the United States.
Numerous studies have documented the negative associations
be-
tween low family socioeconomic status (SES) and ethnic
minority
status on children’s language development (Dearing,
McCartney,
& Taylor, 2001; Elardo, Bradley, & Caldwell, 1977; Johnson,
2001; Siegel, 1982; Walker, Greenwood, Hart, & Carta, 1994).
However, in contemporary Western societies, SES and race are
often confounded (Skiba, Poloni-Staudinger, Simmons, Feggins-
Azziz, & Chung, 2005), making it difficult to examine the
unique
effects of either variable. In addition, proximal processes in the
home influence children’s cognitive outcomes, and research
sug-
gests that the effects of parenting practices may vary by cultural
context (Baumrind, 1972; Deater-Deckard & Dodge, 1997;
Dorn-
busch, Ritter, Leiderman, Roberts, & Fraleigh, 1987; Garcia
Coll,
1990; Garcia Coll et al., 1996). The current study adds to our
understanding of this topic by investigating the associations be -
tween SES, race, and parenting and young children’s language

development over time in a sample selected to reduce the
typical
confound between SES and race; by examining the unique asso-
ciations between maternal sensitivity and negative intrusive be-
haviors with receptive and expressive abilities; and by
exploring
whether the associations between parenting and language out-
comes are moderated by SES and race.
SES, Race, and Language Development
Researchers have consistently found associations between high-
risk demographic factors, such as SES and minority status, and
language outcomes in young children. One of the earliest
studies
on this topic was Hart and Risley’s (1992, 1995) longitudinal
observations of 40 African American and European American
parents from various socioeconomic backgrounds interacting
with
their infants. Demographic variables were linked to children’s
36-month IQ scores and language ability. Specifically, lower
SES
parents, all of whom were African American, had children with
the
lowest language skills and shortest mean length of utterance
com-
pared with children displaying more advanced language skills,
who were predominantly European American and from higher
SES families. Consistent with these findings, Lawrence (1997)
found that middle-class and European American preschool chil-
Elizabeth P. Pungello, Iheoma U. Iruka, and Aryn M. Dotterer,
Frank
Porter Graham Child Development Institute, University of North
Carolina
at Chapel Hill; Roger Mills-Koonce, Center for Developmental

Science,
University of North Carolina at Chapel Hill; J. Steven Reznick,
Frank
Porter Graham Child Development Institute and Department of
Psychol-
ogy, University of North Carolina at Chapel Hill.
Aryn M. Dotterer is now at the Department of Child
Development and
Family Studies, Purdue University.
Correspondence concerning this article should be addressed to
Elizabeth
P. Pungello, Frank Porter Graham Child Development Institute,
University
of North Carolina at Chapel Hill CB# 8180, 105 Smith Level
Road, Chapel
Hill, NC 27599-8180. E-mail: [email protected]
Developmental Psychology © 2009 American Psychological
Association
2009, Vol. 45, No. 2, 544 –557 0012-1649/09/$12.00 DOI:
10.1037/a0013917
544
dren had longer mean lengths of utterance than African
American
and working-class children on tasks requiring children to label
and
provide additional information about a particular picture. Simi -
larly, Raviv, Kessenich, and Morrison (2004) examined the
1,016
families of the NICHD Study of Early Child Care and found that
SES was significantly associated with children’s language

ability
at 36 months.
Identifying the unique relationships between children’s out-
comes and SES and race has been difficult because of the usual
confounding of these variables in the societies where most of
the
research has been conducted. In most studies using diverse sam-
ples, African Americans have been more likely to be of lower
SES
than other racial groups (McLoyd, 1998; McLoyd & Ceballo,
1998; Skiba et al., 2005). The U.S. Census Bureau reported that
in
2005, 33% of African American children under the age of 18
years
old were living in homes rated as “below poverty,” compared
with
less than 10% of European American children (Denavas-Walt,
Proctor, & Lee, 2006). In addition, this report found that
African
Americans had the lowest median household income compared
with European American, Asian, and Hispanic households.
Given
this confounding and the use of traditional sampling techniques,
determining whether associations with language are due to SES
or
to race has been virtually impossible, and both relationships are
theoretically plausible. Whereas a lack of resources and
opportu-
nities because of low family SES and the other stressors that are
associated with poverty may affect children’s outcomes (Evans,
2004), discrimination and racism experienced by ethnic
minority
families may also negatively influence children’s development
(Murry, Brown, Brody, Cutrona, & Simons, 2001; Prelow,
Danoff-

Burg, Swenson, & Pugliano, 2004). We examined the links
between SES and race with children’s receptive and expressive
language between 18 and 36 months in a sample in which the
typical confound between SES and race was reduced to explore
the possible differing associations with SES and race. Given
that 18 to 36 months is a time when adaptive or maladaptive
development begins (Shaw et al., 1998), a greater understand-
ing of the unique relationships between these demographic
variables and children’s language outcomes may have impor-
tant implications for programs aimed at enhancing the school
readiness of children at high risk for poor academic outcomes
because of environmental circumstances.
Parenting and Language Development
In addition to the demographic factors of SES and race, parent-
ing practices have also been related to children’s language
devel-
opment (Burchinal, Campbell, Bryant, Wasik, & Ramey, 1997;
Elardo et al., 1977; Hart & Risley 1992; Linver, Brooks-Gunn,
&
Kohen, 2002; Mistry, Biesanz, Taylor, Burchinal, & Cox, 2004;
Tamis-LeMonda, Bornstein, & Baumwell, 2001). Among the
many relevant parenting factors that have been investigated are
sensitivity (i.e., responsive caregiving and interactions) and
nega-
tive intrusive behaviors (i.e., intrusive, controlling, and punitive
interactions).
Sensitive parenting has been linked with positive child out-
comes, including early language knowledge and literacy
develop-
ment (Birch & Ladd, 1996; Dodici, Draper, & Peterson, 2003;
Pianta, 1997; Pianta, Nimetz, & Bennett, 1997; Pianta & Walsh,
1996). A responsive and emotionally supportive parent provides
an

interactive environment for young children to engage in
reciprocal
verbal and nonverbal exchanges that are stimulating and
rewarding
for the child. Tamis-LeMonda et al. (2001) found that maternal
responsiveness was associated with the achievement of language
milestones during infancy and early toddlerhood, and Mistry et
al.
(2004) found that maternal sensitivity was significantly
associated
with expressive and comprehensive language skills at 36 months
of age. Similarly, Raviv et al. (2004) found that both maternal
sensitivity and cognitive stimulation were independently related
to
36-month-old children’s language outcomes.
Negative intrusive parenting has received less attention in stud-
ies of early language development. This dimension of parenting
behavior focuses on the degree to which the parent interferes
with
the child’s needs, interests, or behaviors, above and beyond the
developmental or safety needs of the child. Intrusive and
control-
ling behaviors (such as unnecessarily restraining the child,
consis-
tently disrupting the child’s efforts with his or her own bids for
attention, or verbally controlling the child with repeated and un-
necessary direction) reflect the parent’s imposition of his or her
own agenda onto the child and his or her failure to understand
and
recognize the child’s effort to gain autonomy and self-efficacy
(Egeland, Pianta, & O’Brien, 1993). Characterized by highly
con-
trolling and negative behavior directed toward the child,
negative

intrusiveness can undermine children’s autonomy and
confidence
and has been linked to negative child outcomes, including
regula-
tory and socioemotional problems (Heller & Baker, 2000;
Mistry,
Melsch, & Taheri-Kenari, 2003; Rubin, Burgess, Sawyer, &
Hast-
ings, 2003) and lower academic achievement (Culp, Hubbs-Tait,
Cuilp, & Starost, 2001). The limited research on early language
development and negative intrusive parenting has produced
mixed
results, with some studies suggesting that links with negative
intrusive parenting are accounted for by maternal sensitivity
and
other studies suggesting that maternal negative intrusiveness
and
maternal sensitivity have independent associations with
language
outcomes. Tamis-LeMonda, Shannon, Cabrera, and Lamb (2004)
found that negative intrusive parenting was related to child lan-
guage outcomes at 24 and 36 months of age, but these were
subsumed by parental sensitivity. In contrast, Keown,
Woodward,
and Field (2001) found that both sensitivity and negative intru-
siveness had independent relations with preschoolers’ language
comprehension and expression. Furthermore, their findings indi -
cated that negative intrusive behavior accounted for differences
in
comprehension and expression scores between children of
teenage
and comparison mothers. These findings suggest that maternal
sensitivity and negative intrusive parenting may contribute
inde-
pendently to early language development and that their
contribu-

tions may differ depending on developmental timing and
environ-
mental context. Thus, another goal of this study was to examine
the separate links of maternal sensitivity and negative intrusive
behaviors with early language development.
SES, Race, Parenting, and Language Development
Although theory and research suggests that sensitive and nega-
tive parent– child interactions influence young children’s
language
outcomes in general, their relations with children’s development
may vary by race (Garcia Coll, 1990; Garcia Coll et al., 1996).
For
example, the associations between negative intrusive parent–
child
interactions may be stronger for European American children
than
545SES, RACE, PARENTING, AND LANGUAGE
DEVELOPMENT
for children in other racial and ethnic groups (see review by
Bugental & Grusec, 2006; Deater-Deckard & Dodge, 1997). Ispa
et al. (2004) found that parent intrusiveness predicted 25-month
negativity for European American children. However, for
African
American children, parent intrusiveness predicted 25-month
neg-
ativity when parents exhibited low levels of warmth. Further,
certain parenting practices may be more or less adaptive
depending
on the settings in which children are raised (e.g., setting strict
limits on children who live in a dangerous environment; see

Parke
& Buriel, 2006). Thus, another goal of this study was to
investigate
whether the associations between parenting and young
children’s
language outcomes vary by SES and race.
Current Study
A convenience sample in a contemporary Western society
would inevitably confound family SES and racial status.
Statistical
controls can be applied, but they must be interpreted in a
nebulous
counterfactual conditional frame in which complex aspects of
life
(e.g., family income, education) are treated as model parameters
that can be raised or lowered independently of other variables.
We
used an alternative strategy, which was possible because the re-
search was conducted in a city in the southeastern United States
in
which an economically diverse group of African Americans and
European Americans could be selected. The main goals of the
study were to use this unique sample (a) to examine the associa-
tions between SES (measured on the basis of income and
maternal
education) and race (measured as a self-reported category) and
early language development (measured using a standardized test
of
receptive and expressive abilities) from 18 through 36 months,
(b)
to investigate the separate links of maternal sensitivity and
nega-
tive intrusive parenting (measured using detailed analysis of
vid-

eotapes recorded during mother– child interactions in a
laboratory)
with these outcomes, and (c) to explore whether SES and race
moderate the relations between these parent– child proximal
pro-
cesses and children’s language outcomes.
Method
Participants
Participants were drawn from a largely urban community via
fliers and postings at birth and parenting classes, as well as
through
mailings and phone contact inviting participation in a
longitudinal
study of child health and development. To reduce the typical
confound between SES and race, recruitment was focused on
four
groups: African American middle-income, African American
low-
income, European American middle-income, and European
Amer-
ican low-income families (these groups were used to guide
recruit-
ment only, not for analytic purposes). A total of 206 families
comprised the full sample. Of these, 25 families either withdrew
or
were dropped because they were missing one or more scores for
predictor variables. These 25 families were compared with those
retained in the sample to determine whether they differed on
background characteristics; no significant differences were
found
for race, SES, or maternal age.
Despite recruitment goals, preliminary analyses revealed that

African American families were overrepresented in the low end
of
the SES distribution and European American families were
over-
represented in the high end of the SES distribution (the creation
of
the SES variable is described below). Thus, the effects of
income
and race could not be separated in the extremes of the
distribution
range. Given our goal of examining the effects of income and
race
in a sample in which the confounding of these variables was
reduced, we focused on a constrained range of social strata for
which we had adequate data to make racial comparisons. Specif-
ically, to ensure that the shape of the SES distribution was
similar
for each racial group, we dropped the outliers in portions of the
SES distribution in which there was little or no overlap for
African
American and European American families and focused our
anal-
yses on a sample in which there was considerable overlap in the
SES distribution. This constraint eliminated 31 African
American
families and 1 European American family with very low SES (a
value of less than �2.41 on our SES scale, described below) and
3 European American families with very high SES (a value
greater
than 6.00 on our SES scale). In addition to differing i n terms of
SES, mothers from the 35 excluded families were younger (M �
24.73 years, SD � 5.26, range � 18 –37 years vs. M � 28.78
years, SD � 5.53, range � 18 – 40 years) compared with the
146
families included in the analyses.

Of the 146 families retained for analysis, 50% (n � 73) were
African American and 50% (n � 73) were European American.
The sex distribution of children was comparable across the race
groups, with 48% of the European American children being fe-
males and 52% of the African American children being females.
At the 18-month time point (the time point at which language
assessments began), maternal average years of education was
14.78 years (SD � 2.10, range � 10 –20 years) for African
Americans and 15.30 years (SD � 2.16, range � 10 –20 years)
for
European Americans; the difference was not significant, t(144)
�
1.51, p � .13. On our SES scale, at the 18-month time point, the
mean was 0.18 (SD � 1.82, range � �2.38 – 4.80) for African
American families and 0.61 (SD � 1.98, range � �2.23– 4.70)
for
European American families; the difference was not significant,
t(144) � 1.44, p � .15. To put this in context, the range for this
SES variable was �2.38 to 4.80, with a mean of 0.42. The
average
family size was approximately four and ranged from 3.71 at 12
months for European American families to 4.12 at 36 months
for
African American families; family size was also not
significantly
different across racial groups. In contrast, marital status and
race
were not independent, �2(3, 146) � 10.68, p � .05; European
American families were more likely to be married or cohabiting
(90% of European American compared with 70% of African
American families; a total of seven families in each group were
classified as cohabitating specifically) and African American
fam-
ilies were more likely to be single, never married (26% of
African

American compared with 8% of European American families).
Measures and Procedure
SES. Mothers provided information on family income and
their education level at child ages 6, 12, 30, and 36 months.
Each
family’s income-to-needs ratio (INR) was computed by dividing
the total family income by the poverty threshold for the
appropri-
ate family size, as determined by the U.S. Department of Health
and Human Services. Repeated-measures analysis of variances
revealed no race differences in INR or education at any of the
time points and no overall Race � Time interactions for INR,
546 PUNGELLO ET AL.
F(1, 116) � 1.37, p � .24, and for education, F(1, 116) � 2.27,
p � .13. An index for SES was created by standardizing INR
and
maternal education level and taking the average of these
variables
across the time points. Bivariate correlations of SES across the
four time points revealed consistency across time, with stability
coefficients ranging from .78 to .92.
Language development. The Preschool Language Scale– 4
(Zimmerman, Steiner, & Pond, 2002) is composed of two sub-
scales: the Auditory Comprehension subscale that evaluates
what
children know or understand but may not say and the Expressi ve
Communication subscale that evaluates what children say. Care
was taken in the development of this measure to ensure its
validity

for use with different racial groups. The standardization sample
was composed of a diverse sample (39.1% ethnic minority
children
included); experts reviewed all items for ethnic, gender, and so-
cioeconomic bias; and statistical procedures tested for item bias
(Zimmerman, Steiner, & Pond, 2004).
The tasks designed to assess auditory comprehension for tod-
dlers focus on skills considered important precursors for
language
development, such as attention to speakers (e.g., looks at
objects or
people the caregiver calls attention to) and appropriate object
play
(e.g., demonstrates appropriate use of play materials including a
ball). Tasks designed to assess auditory comprehension for
preschool-aged children focus on comprehension of basic
vocab-
ulary (e.g., parts of the body including the nose), concepts (e.g.,
spatial concepts including “in”), and grammatical markers (e.g.,
pronouns including “me”). The tasks designed to assess
expressive
communication in toddlers focus on vocal development (e.g.,
produces different types of vowel– consonant sounds) and social
communication (e.g., uses vocalizations and gestures to request
toys or food). Tasks designed to assess expressive
communication
in preschool-aged children ask children to name common
objects
(e.g., ball), use concepts that describe objects and express
quantity
(e.g., how many chicks there are in a picture), and use specific
prepositions, grammatical markers (e.g., verb � -ing), and sen-
tence structures (e.g., produces basic four to five word
sentences).

Children’s expressive communication and auditory comprehen-
sion were assessed at 18, 24, 30, and 36 months during testing
sessions conducted in a laboratory that the child had visited
several
times before. The Preschool Language Scale– 4 correlates with
other standard measures of language development, with internal
consistencies ranging from .67 to .88 for the subscales and test–
retest reliabilities ranging from .82 to .95. In the present data,
the
internal consistencies (Kuder–Richardson 20) for the subscales
ranged from .77 to .84 for Auditory Comprehension and from
.72
to .82 for Expressive Communication across the four time
points.
Age equivalent scores were used in the current analyses, given
the
interest in examining growth in language over time.
Parenting behaviors. Maternal behavior was observed during
a 10-min semi-structured mother– child free play episode at 12
months of child age and during a 10-min puzzle completion task
at
24 months of child age. Both tasks were conducted during labo-
ratory visits with the mother and child. For the free play task,
mothers and children were presented with a standardized set of
toys and asked to play as they normally would during the day;
the
interaction lasted for 10 min. For the puzzle task, mothers and
children were seated at a table, a puzzle was placed before
them,
and the pieces were removed. Mothers were informed that this
was
a task for the child but that they could help in any way they
wanted. After the completion of the first puzzle, a second (and
third if necessary) puzzle of increasing difficulty was given to

the
child. If the third puzzle was completed before the 10 min had
passed, then the mother was asked to continue playing with the
child and third puzzle for the remainder of the time. The
mother–
child interactions at each time point were videotaped for later
coding.
Trained and reliable coders assessed seven dimensions of ma-
ternal behavior adapted from Egeland and Heister (1995) and
the
NICHD Early Child Care Research Network (1997). Each
behav-
ioral dimension was double coded on a 5-point scale at 12
months
and a 7-point scale at 24 months (for the current analyses, the
7-point scale was calibrated to make it comparable with a 5-
point
range and distribution). Interrater disparities were resolved by
conferencing. Coders were not race matched with participant
fam-
ilies; rather, African American and European American coders
were randomly assigned. Every pair of coders maintained a min-
imum .80 intraclass correlation on each dimension, which
included
the following: (a) a global sensitivity scale that rated the
mother’s
responses to the child’s signals of emotional and physical needs
(e.g., responds warmly to child bids and anticipates the physical
and emotional needs of her child), (b) an intrusiveness scale
that
rated the degree to which the mother imposed her agenda on her
child (e.g., physically restraining the child or dominating the
interaction with unnecessary verbal direction), (c) a detachment
scale that rated the mother’s emotional involvement and degree
of

physical activity with the child (e.g., rarely making eye contact,
verbal interaction, or responses to children’s bids), (d) a
positive
regard scale that measured the mother’s positive affect and
delight
in interacting with her child (e.g., warm vocal tone, physical
affection, and smiling), (e) a negative regard scale that rated
maternal expressions of negative affect and behaviors toward
the
child (e.g., disapproval, harsh physical manipulation,
unexplained
punishment), (f) an animation scale that rated the mother’s
enthu-
siasm for her child (e.g., enthusiastic vocal tone and facial
anima-
tion), and (g) a stimulation of development scale that rated
moth-
er’s cognitive stimulation of the child (e.g., labeling materials,
encouraging verbalizations, and relating ongoing activities to
be-
yond the current context). The validity of these dimensions is
supported by work demonstrating their convergent validity with
other measures of the home environment, such as the Home
Observation for Measurement of the Environment (NICHD
Early
Child Care Research Network, 2006), as well as their predictive
validity within socioeconomically and ethnically diverse
samples
(Blair et al., 2008; Garrett-Peters, Mills-Koonce, Vernon-
Feagans,
Willoughby, & Cox, 2008; Mills-Koonce et al., 2007) and
specif-
ically within African American subsamples (Propper,
Willoughby,
Halpern, Cox, & Carbone, 2007).

From the 12-month observations, composite variables were con-
structed from these scales on the basis of a principal factor
analysis
followed by a promax (oblique) rotation for identifying patterns
of
underlying structure. A scree test suggested only two
meaningful
factors. In interpreting the rotated factor pattern, an item was
said
to load on a given factor if the loading was .40 or greater for
that
factor and was less than .40 for any other factor. Using these
criteria, five items loaded on the first factor and two items
loaded
on the second factor. An overall composite for sensitive
parenting
was created by summing the global sensitivity, detachment (re-
versed), positive regard, animation, and stimulation of develop-
DEVELOPMENT
ment dimensions (factor loadings were .94, .78, .84, .62, and
.85,
respectively). An overall composite for negative intrusive
behavior
was created by summing the intrusiveness and negative regard
dimensions (factor loadings were .61 and .67, respectively). The
intraclass correlations for the sensitivity and negative intrusive
composites were .90 and .85, respectively. At 24 months, a con-
firmatory factor analysis obtained the same factors, and a sensi -
tivity composite and a negative intrusive composite were thus
created using the same dimensions at 24 months. The scores for
the

12- and 24-month sensitive parenting composites were averaged
to
create the sensitive parenting score used in the current analyses,
as
were the 12- and 24-month scores for the negative intrusive
behaviors.
Results
Preliminary Analyses
Table 1 provides the means, standard deviations, and ranges
for each of the parenting factors, the Auditory Comprehension
scores, and the Expressive Language scores for the two race
groups. Table 2 provides the cross-time stability in auditory
comprehension and in expressive communication, which ranged
from moderate to high. The extent to which the parenting
variables were related to one another was also examined; ma-
ternal sensitivity was negatively correlated with maternal neg-
ative intrusiveness (r � �.58, p � .001).
Model Specification
Hierarchical linear models were estimated using the mixed
procedure (i.e., proc mixed) in SAS software (Version 9.1) in
order
to examine changes in children’s language development over
four
time points from 18 to 36 months. This procedure allowed for
the
control of the nonindependence of observations due to the same
individuals being repeatedly assessed over time. A hierarchical
linear model approach also accounts for missing-at-random out-
come data, allowing the use of all available data for the
outcome
of interest (Little & Rubin, 1987; Raudenbush & Bryk, 2002).

Restricted maximum likelihood was used in reporting model pa-
rameters, and degrees of freedom were estimated using the
Satter-
thwaite method. Child’s age was centered at the first
measurement
occasion, thus the intercept represented the outcome (auditory
comprehension or expressive communication) at 18 months in
all
models. The linear slope parameter (child’s age) represented the
rate of change in auditory comprehension and expressive
commu-
nication, and the quadratic slope parameter (child’s age2) repre -
sented a change in the rate of change (acceleration–
deceleration).
The extent to which the developmental pattern of auditory com-
prehension and expressive communication varied as a function
of
family SES, race, maternal sensitivity, and maternal negative
in-
trusiveness was also examined (child sex was also added as a
covariate in the models). Significant interactions were probed
with
procedures outlined by Aiken and West (1991).
Auditory Comprehension
To examine changes in auditory comprehension from 18 to 36
months, we evaluated both fixed and random age effects by esti-
mating a series of unconditional growth models. In these growth
models, we tested whether the overall trajectory of auditory
com-
prehension was best characterized by linear or quadratic
patterns
of change and whether each coefficient should be treated as
random or fixed. The final growth model for auditory

comprehen-
sion included fixed linear and quadratic terms and a random
intercept. We did not include random linear or quadratic slopes
because of those terms being close to zero (thus inestimable)
and
because the recommendation has been to remove those terms
from
the model (Searle, Casella, & McCulloch, 1992).
Next, we evaluated the extent to which auditory comprehension
varied as a function of SES, race, and mother– child
interactions.
Table 3 provides estimates and standard errors for the uncondi -
tional and final models predicting children’s auditory
comprehen-
sion skills over time. A significant main effect for race
indicated
that European American children’s performance on auditory
com-
prehension (M � 20.35) was somewhat higher than that of
African
Table 1
Descriptive Statistics for Parenting Factors and Language
Outcomes by Race
Variable
African American
(n � 73)
European American
(n � 73)
Sensitivity
M �0.25 0.25

SD 0.81 0.79
Range �2.42–1.59 �1.82–1.53
Negative intrusive
M 0.30 �0.34
SD 0.81 0.62
Range �1.24–3.02 �1.67–1.27
Auditory comprehension
18 months
M 16.47 20.30
SD 2.93 4.58
Range 13–22 13–29
24 months
M 22.30 27.16
SD 5.13 6.51
Range 13–33 13–41
30 months
M 29.80 37.79
SD 8.01 8.90
Range 15–51 20–60
36 months
M 38.71 46.99
SD 9.37 12.18
Range 15–66 15–75
Expressive communication
18 months
M 20.90 21.22
SD 2.50 2.53
Range 12–26 11–26

24 months
M 24.17 26.00
SD 3.12 4.63
Range 15–35 15–41
30 months
M 30.25 37.34
SD 5.92 7.36
Range 17–45 21–52
36 months
M 37.78 43.91
SD 9.37 7.52
Range 20–55 26–63
548 PUNGELLO ET AL.
American children (M � 17.64). The linear slope reflected
positive
linear change averaging 1.11 points per month; however, this
effect was qualified by a significant quadratic effect and
indicated
that the rate of growth accelerated after 24 months. This pattern
of
growth did not differ by race.
Maternal sensitivity and negative intrusive parenting were also
examined as predictors of changes in auditory comprehension.
A
significant Age � Sensitivity interaction indicated that
children’s
growth in auditory comprehension occurred at a faster rate when
their mothers were more sensitive (see Table 3). As pictured in

Figure 1, children with high sensitivity mothers (1 standard
devi-
ation above the mean) had higher auditory comprehension
scores
and demonstrated a faster rate of growth over time than children
with low sensitivity mothers (1 standard deviation below the
mean). These effects did not differ by SES or race. Similar to
maternal sensitivity, although there was no main effect for
mater-
nal negative intrusiveness, a significant Age � Negative
Intrusive-
ness interaction emerged, indicating that as negative
intrusiveness
increased, the rate of growth decreased. As pictured in Figure 2,
children with high negative intrusiveness mothers (1 standard
deviation above the mean) had slower rates of growth over time
than those with low negative intrusiveness mothers (1 standard
deviation below the mean). This effect did not differ by SES or
race.
The proportion of variance accounted for was calculated accord-
ing to Snijders and Bosker (1999). The baseline for comparison
was the unconditional growth model (Hox, 2002). The final
model
for auditory comprehensi on accounted for approximately 38% of
the within-person (Level 1) variance and 48% of the between-
person (Level 2) variance.
Expressive Communication
To examine changes in children’s expressive communication
from 18 to 36 months, we evaluated both fixed and random age
effects by estimating a series of unconditional growth models.
In
these growth models, we tested whether the overall trajectory of
expressive communication was best characterized by linear or

quadratic patterns of change and whether each coefficient
should
be treated as random or fixed. The final growth model for
expres-
sive communication included fixed linear and quadratic terms
and
a random intercept. We did not include random linear or
quadratic
slopes because of those terms being close to zero (thus
inestima-
ble) and because the recommendation has been to remove those
terms from the model (Searle et al., 1992).
Next, we evaluated the extent to which expressive communica-
tion varied as a function of SES, race, and mother– child
interac-
tions. Table 4 provides estimates and standard errors for the
unconditional and final models predicting children’s expressive
communication skills over time. The intercept for expressive
com-
munication was 21.48, indicating that 18-month-old children
scored 3 months higher than their age-expected scores. The
linear
slope for expressive communication reflected positive change
av-
eraging 0.55 points per month. However, this effect was
qualified
by a significant quadratic effect and indicated that the rate of
growth accelerated. This effect was further qualified by a
signifi-
cant Quadratic � Race effect. As shown in Figure 3, although
there was slower initial growth in expressive communication for
African American children, the rate of change occurred at a
faster
rate for African American children. In addition, a significant

effect
for Age � SES (see Table 4) indicated that expressive
communi-
cation occurred at a faster rate for children in high SES families
(1
standard deviation above the mean) compared with children in
low
SES families (1 standard deviation below the mean; see Figure
4).
Maternal sensitivity and negative intrusive parenting were also
significant predictors of expressive communication. A signifi -
cant Sensitivity � Age effect indicated that children with high
sensitivity mothers (1 standard deviation above the mean) dem-
onstrated a faster rate of growth over time than children with
low sensitivity mothers (1 standard deviation below the mean;
see Figure 5). Finally, as shown in Table 4, although the main
Table 2
Cross-Time Stability in Auditory Comprehension (Above the
Diagonal) and Expressive Communication (Below the Diagonal)
Variable 1 2 3 4
1. 18 months — .68 .66 .63
2. 24 months .50 — .74 .77
3. 30 months .39 .64 — .83
4. 36 months .39 .60 .85 —
Note. N � 146. All values are significant at p � .001.
Table 3
Unconditional and Final Hierarchical Linear Model (HLM)
Results Predicting Children’s Auditory Comprehension
(N � 146)

Unconditional
growth model Final HLM
Variable B SE B SE
Intercept 18.03�� 0.68 17.64�� 0.90
Age (linear slope) 1.10�� 0.12 1.11�� 0.11
Age2 (quadratic slope) 0.02�� 0.01 0.02�� 0.01
Sex �2.65� 0.87
Race 2.71� 1.11
SES 0.74 0.40
Race � SES �0.38 0.51
Age � Race 0.08 0.07
Age � SES 0.03 0.02
Age2 � Race �0.01 0.01
Sensitivity 0.12 1.03
Sensitivity � Race 0.98 1.38
Sensitivity � SES 0.19 0.34
Sensitivity � Age 0.17� 0.05
Negative intrusive 0.17 1.04
Negative Intrusive � Race �1.59 1.66
Negative Intrusive � SES 0.26 0.41
Negative Intrusive � Age �0.13� 0.05
Unconditional
Variance component Variance SE Variance SE
Residual 24.84�� 1.73 20.75�� 1.46
Intercept 43.24�� 5.84 20.10�� 3.15
Note. SES � socioeconomic status.
� p � .05. �� p � .01. �� p � .001.

DEVELOPMENT
effect for maternal negative intrusiveness was not significant, a
significant three-way interaction emerged between age, nega-
tive intrusive parenting, and race. As shown in Figure 6, race
moderated the association between negative intrusive parenting
behaviors and children’s growth in expressive language, such
that this relation was stronger for European American children
than for African American children. Follow-up comparisons
indicated that the association with negative intrusive parenting
was not significant for African American families. In contrast,
the relation was significant for European American families,
with the difference in expressive language between high (1
standard deviation above the mean) and low (1 standard devi-
ation below the mean) negative intrusive parenting increasing
over time.
15
20
25
30
35
40
45
63034281

Age in Months
A
u
d
it
o
ry
C
o
m
p
re
h
e
n
si
o
n
High Sensitivity
Low Sensitivity
Figure 1. Auditory comprehension as a function of time and
sensitivity.
15
20

25
30
35
40
45
63034281
Age in Months
A
u
d
ito
ry
C
o
m
p
re
h
e
n
si

o
n
High Negative/Intrusive
Low Negative/Intrusive
Figure 2. Auditory comprehension as a function of time and
negative intrusiveness.
550 PUNGELLO ET AL.
The proportion of variance accounted for was calculated accord-
ing to Snijders and Bosker (1999). The baseline for comparison
was the unconditional growth model (Hox, 2002). The model for
expressive communication accounted for approximately 40% of
the within-person (Level 1) variance and 53% of the between-
person (Level 2) variance.
Discussion
Our main goal was to examine the associations between SES
(based on income and maternal education), race, and parenting
and
language development longitudinally in early childhood in a
sam-
ple in which the typical confound between SES and race was
reduced. SES, race, maternal sensitivity, and negative intrusive-
ness were significant predictors of language outcomes in young
children. These findings add to the literature by examining the
links between SES and race over time with both receptive and
expressive abilities, by investigating the separate associations
of
maternal sensitivity and negative intrusive parenting with early

language development, and by exploring the possible
moderating
effects of SES and race on the links between these parenting
behaviors and language development. The pattern of results sug-
gests that (a) race is associated with receptive language skills,
(b)
both SES and race are independently related to the growth of
expressive skills, (c) both maternal sensitivity and negative
intru-
sive parenting have unique links with language development,
and
(d) race moderates the relation between negative intrusive
parent-
ing and expressive language development.
The current findings demonstrate the association between SES
and language skills. Children in lower SES families
demonstrated
a slower rate of growth for expressive language skills compared
with children in higher SES families. This pattern is consistent
with past studies that have assessed the relations of SES and
income with young children’s functioning and development, in-
cluding language development (Duncan, Brooks-Gunn, & Kle-
banov, 1994; Hoff-Ginsberg, 1991; Linver et al., 2002;
McLoyd,
1998). Parental proximal factors associated with low SES likely
account for part of this association. Mistry et al. (2004) noted
that
perception of financial resource availability was related to
mater-
nal depression and less positive mother– child interactions,
which,
in turn, affected children’s cognitive and language development.
Hoff (2003) demonstrated that the differences in growth in
vocab-

ulary between higher SES and lower SES children (ages 16 –31
months) was fully accounted for by maternal speech, with
higher
SES mothers speaking in longer utterances, using richer vocabu-
lary, and producing more complex sentences than lower SES
mothers. Additional qualitative and quantitative research is
needed
to identify other specific mechanisms associated with SES that
have a direct influence on child language.
Race was also linked to language outcomes. African American
children scored lower, on average, than European American
chil-
dren on receptive language skills, and African American
children
demonstrated a slower rate of growth than European American
children for expressive skills. In addition, although African
Amer-
ican children demonstrated slower initial growth in expressive
communication, their rate of acceleration was faster than
European
American children; however, European American children re-
mained higher than African American children. Several factors
may account for these findings. First, cultural differences in the
way children are spoken to may affect language skills. In a
study
investigating joint book-reading strategies, Anderson-Yockel
and
Haynes (1994) found that working-class African American
moth-
ers were less likely to ask questions that would elicit responses
from their toddler and concluded that “. . .[Black] children are
not
seen as information givers or question-answerers. This is espe-
cially true of questions for which adults already have an
answer”

(p. 592). Thus, in comparison with European American mothers
who are more likely to elicit answers from their child through
yes–no and “what happened?” questions, African American
moth-
ers appear to be less likely to engage in the probing that could
possibly enhance their children’s expressive language. The
present
results raise the possibility that this association is not
associated
with SES per se but may reflect a broader cultural difference in
parenting style.
The associations with race found here could also be related to
racial discrimination and prejudice. Murry et al. (2001) investi -
gated the moderating effect of racial discrimination on African
American’s psychological functioning and family relationships.
They found that though the lack of income and resources was a
significant factor in families’ stress and functioning, “simply
being
Black in America” (Murry et al., 2001, p. 917) also played an
important, but often unacknowledged, role in mother’s anxiety
and
Table 4
Unconditional and Final Hierarchical Linear Model (HLM)
Results Predicting Children’s Expressive Communication
(N � 146)
Unconditional
Variable B SE B SE
Intercept 20.57�� 0.50 21.48�� 0.67
Age (linear slope) 0.78�� 0.10 0.55�� 0.11
Age2 (quadratic slope) 0.02�� 0.01 0.03�� 0.01

Sex �1.77� 0.62
Race �0.57 0.88
SES 0.32 0.29
Race � SES �0.35 0.36
Age � Race 0.61�� 0.17
Age � SES 0.06�� 0.01
Age2 � Race �0.02� 0.01
Sensitivity 0.29 0.74
Sensitivity � Race 0.12 0.98
Sensitivity � SES 0.16 0.25
Sensitivity � Age 0.14� 0.04
Negative intrusive 0.25 0.77
Negative Intrusive � Race 0.35 1.31
Negative Intrusive � SES �0.01 0.29
Negative Intrusive � Age �0.02 0.05
Negative Intrusive � Age � Race �0.15� 0.07
Unconditional
Variance component Variance SE Variance SE
Residual 18.26�� 1.27 13.06�� 0.92
Intercept 18.16�� 2.68 9.36�� 1.58
Note. SES � socioeconomic status.
� p � .05. �� p � .001.
DEVELOPMENT
depression levels, thus influencing the quality of the mother –
child
interaction and relationship.

In addition, the association with race found here could be
related
to other financial and resource variables not assessed. That is,
although the confound between SES and race was reduced in
this
sample, the racial groups may still have differed in other
resources
and opportunities that could have influenced children’s
outcomes
(McLoyd & Ceballo, 1998). Relatedly, marital status may have
also played a role in the association between race and language
outcomes found in this study. Even after reducing the confound
between race and SES, marital status was associated with race
such
that African American children were less likely to be in homes
with married or cohabitating parents compared with European
American children. Prior work has demonstrated associations
be-
tween marital status and young children’s language outcomes,
although the effects of marital status were found to be weaker
than
15
20
25
30
35
40

45
63034281
E
xp
re
ss
iv
e
C
o
m
m
u
n
ic
a
tio
n
Age in Months
African American
European American
Figure 3. Expressive communication as a function of time and
race.

15
20
25
30
35
40
45
63034281
Age in Months
E
xp
re
ss
iv
e
C
o
m
m
u
n

ic
a
ti
o
n
High SES
Low SES
socioeconomic status (SES).
552 PUNGELLO ET AL.
those of maternal education (Qi, Kaiser, Milan, & Hancock,
2006).
An important direction for future work is to examine how the
association between marital status and race may contribute to
the
relation between race and children’s language outcomes,
investi-
gating economic factors associated with marital status as well as
the relation between family structure and the language environ-
ment experienced by the child.
Finally, it is also possible that the associations between race
and
language observed in this study were constrained by cultural
aspects of the language assessment measure per se. African
Amer-
ican children may, in general, have as their primary input a

variety
of language that is structurally different from European
American
children’s, and the standardized measure used in this study may
have reflected this difference as a deficit. That is, differences in
language input may have also contributed to the language
disparity
between European American and African American children
found in this study. Because standardized measures are based on
Standard American English (SAE), children’s usage of African
American English (AAE) are discounted and penalized, possibly
leading to lower language performances (Craig, Thompson,
Wash-
ington, & Potter, 2004; Thompson, Craig, & Washington, 2004).
The results found here may thus indicate that African American
children use a variety of English that is different from SAE
rather
than reflecting a delay in language development. Indeed, Craig
et
al. (2004) found that when AAE vernacular was not scored as an
error in a standardized reading test, African American
elementary
school children performed significantly better, but this increase
was not educationally significant. Research is needed to
determine
how AAE influences children’s early auditory comprehension
and
expressive language skills, given some evidence that children
with
dialect switching between AAE and SAE may be more cognizant
of language structures and pragmatics (Connor & Craig, 2006).
More broadly, future work should examine the variations in the
language input children hear and use assessment procedures that
account for variations of language that are structurally different
from SAE, such as AAE, to further understand the differences

found here. In contrast, given that SAE is the basis of all
currently
available standardized accountability measures, it is also
important
to examine how well African American children fare on these
standardized assessments compared with their European
American
counterparts to inform the literature on the achievement gap.
Concerning parenting, the present results suggest that both ma-
ternal sensitivity and negative intrusive parenting are related to
language outcomes. The notion that there are multiple
independent
and overlapping processes associated with environmental
support
for language development is consistent with previous studies
that
have found different effects of multiple parenting behaviors on
multiple aspects of child language at multiple time points (e.g.,
Tamis-LeMonda et al., 2004). The finding that maternal
sensitivity
was linked to the growth of both receptive and expressive
language
abilities is consistent with previous literature examining cross -
sectional effects of maternal sensitivity on children’s language
outcomes (e.g., Baumwell, Tamis-LeMonda, & Bornstein, 1997;
Mistry et al., 2004). The present findings expand this literature
by
providing evidence that maternal sensitivity, regardless of race
and
SES, is positively associated with growth in both receptive and
expressive language from 18 through 36 months of age,
typically
an age span of great change in the language domain.
Increased negative intrusive maternal behavior was associated

with a slower rate of growth of receptive language, and the
depressive effect of negative intrusive parenting on the growth
of
expressive language was moderated by race. Specifically,
negative
intrusiveness was linked to the growth of expressive language
for
children from European American families, suggesting that lan-
guage development may be compromised if the caregiver does
not
support the autonomy and development of the child. European
15
20
25
30
35
40
45
63034281
Age in Months
E
xp
re
ss

iv
e
C
o
m
m
u
n
ic
a
tio
n
High Sensitivity
Low Sensitivity
sensitivity.
DEVELOPMENT
American children with mothers that demonstrated high levels
of
negative intrusiveness demonstrated slower rates of growth than
those whose mothers demonstrated low levels of negative intru-
siveness. In contrast, negative intrusiveness did not appear to be
related to the growth of expressive language skills for African
American children. This finding is consistent with past research

that has found a negligible, if not beneficial, impact of more
highly
controlling parenting for African American children,
particularly
in combination with parental warmth (Baldwin, Baldwin, &
Cole,
1990; Brody & Flor, 1998; Ispa et al., 2004; McLoyd & Smith,
2002). Ispa et al. (2004) suggested that the minimal association
between negative intrusive parenting and outcomes for African
American children stems from the possibility that negative
parent-
ing may be buffered by other contextual or parenting factors for
African American families. Also, these behaviors may not have
the
same meaning across cultural groups (Deater-Deckard & Dodge,
1997). Thus, the associations between parenting and the child’s
language development must be evaluated in the broader context
in
which the parenting behaviors occur.
The present study provides an unusual and important perspec-
tive on some associations with early language development.
How-
ever, limitations in the study must be acknowledged. One set of
limitations concerns the generalizability and breadth of the
find-
ings. To ensure that the SES distribution was similar between
the
racial groups and thus reduce the confound between SES and
race,
families at the extreme ends of the SES distribution were
excluded
from the analyses, limiting generalizations to families with very
low or very high SES levels. Given the goal of examining the
separate effects of SES and race, we are confident that the
benefit

gained from reducing this confound was worth the cost of
focusing
on a somewhat limited sample. It must be noted, though, that
even
in this reduced sample, race was not completely unrelated to
variables that can influence SES. The two race groups differed
in
terms of maternal education (although the difference was not
statistically significant) and marital status. Thus, although we
reduced the confound between race and SES as compared with
the
strong correlation between these variables in most other studies
conducted in the United States, our conclusions concerning SES
and race need to be interpreted with some caution.
Also concerning generalizability, our model only predicted En-
glish language development and might not generalize to other
languages. More significantly, we used a language assessment
tool
that tapped SAE and may have underestimated the language
abil-
ities of children who have been exposed to an environment rich
in
AAE. Further, our inability to test for the associations between
maternal speech and language outcomes was a limitation of this
study. Future work could assess maternal speech and use a mea-
sure more sensitive to dialectical variation to examine their
effects
on the relationships investigated in this study.
Another limitation concerns the fact that parenting was
observed
at only two time points and during semi-structured interactions
in
a laboratory setting. Given evidence suggesting that parental

sen-
sitivity can change over time (Hirsh-Pasek & Burchinal, 2006),
future work could examine whether and how changes in
parenting
sensitivity and negative intrusiveness relate to language
develop-
ment and, specifically, whether aspects of parental style have
different effects at different stages of language development.
Also,
examinations of parenting in more naturalistic settings with a
wider range of parenting behaviors and styles of language input
are
necessary to validate the current findings, which were based on
a
more limited window of parenting observations. Finally,
additional
demographic and parenting factors that are likely to i nfluence
young children’s language development should be included in
subsequent research. For example, several studies have found
that
type and quality of child care is associated with children’s
cogni-
tive and language outcomes (e.g., NICHD Early Child Care Re-
15
20
25
30
35
40

45
50
18 24 30 36
Age in Months
E
xp
re
ss
iv
e
C
o
m
m
u
n
ic
a
tio
n
African American, High Negative/Intrusive
African American, Low Negative/Intrusive

European American, Low Negative/Intrusive
European American, High
Figure 6. Expressive communication as a function of time, race,
and negative intrusiveness.
554 PUNGELLO ET AL.
search Network, 2000; Peisner-Feinberg et al., 2001), and
recent
research suggests that father effects on children’s early
language
outcomes may be independent of mother effects (Pancsofar &
Vernon-Feagans, 2006).
Despite these limitations, our results suggest important di -
rections for research on language development and for the
implementation of intervention programs aimed at increasing
the school readiness of children at high risk for poor academic
outcomes. Concerning research on language development, our
findings suggest that SES and race are uniquely related to
children’s language development. Given that these two factors
are often confounded in research in this domain, care should be
taken when results are interpreted. Our findings also suggest
that sensitivity and negative intrusive parenting are not two
sides of the same coin and that each variable has a unique link
with language outcomes. Future work on parenting should
investigate the unique associations between sensitivity and neg-
ative intrusive parenting on other developmental outcomes.
Further, our data suggest that the associations between these
parenting behaviors and child outcomes may vary by racial
group, depending on the developmental outcome being exam-
ined. Future research needs to identify domains in which race

may moderate the effects of parenting and, more importantly,
the mechanisms responsible for these effects. Research is also
needed to examine culturally relevant parenting practices that
are particularly meaningful for at-risk children, such as sup-
portive and strict parenting (i.e., no-nonsense parenting; see
Brody & Flor, 1998). Further, our study focused on complexi-
ties of the environment early in childhood and did not examine
individual differences among children that may make language
learning easier for some children compared with others (e.g.,
phoneme perception, working memory capacity). Future re-
search could test more nuanced models by including perceptual
and cognitive variables to assess individual differences in chil -
dren’s language learning potential and examine how these fac-
tors may interact with maternal sensitivity and negative intru-
sive parenting.
Concerning the implementation of intervention programs, in
addition to providing children with language-rich activities and
materials to help combat the effects of poverty, parent-focused
programs that increase sensitivity may further improve
children’s
language development. Further, parenting interventions should
focus on culturally relevant practices that would benefit
children’s
development. More research is needed concerning the factors
that
contribute to the associations with race found here to make
more
specific programmatic recommendations; however, intervention
programs that are sensitive to the cultural context in which chil -
dren are raised may be more successful in reducing the effects
of
demographic risk factors on children’s development and
possibly
help to reduce the achievement gap.

References
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing
and
interpreting interactions. Thousand Oaks, CA: Sage.
Anderson-Yockel, J., & Haynes, W. O. (1994). Joint book-
reading strate-
gies in working-class African American and White mother–
toddler
dyads. Journal of Speech and Hearing Research, 37, 583–593.
Baldwin, A. L., Baldwin, C., & Cole, R. E. (1990). Stress-
resistant families
and stress-resistant children. In J. Rolf, A. S. Masten, D.
Cicchetti, K.
Neuchterlein, & S. Weintraub (Eds.), Risk and protective
factors in the
development of psychopathology (pp. 257–280). Cambridge,
England:
Cambridge University Press.
Baumrind, D. (1972). An exploratory study of socialization
effects of
Black children: Some Black–White comparison. Child
Development, 43,
261–267.
Baumwell, L., Tamis-LeMonda, C. S., & Bornstein, M. H.
(1997). Mater-
nal verbal sensitivity and child language comprehension. Infant
Behav-
ior and Development, 20, 247–258.
Birch, S. H., & Ladd, G. W. (1996). Interpersonal relationships

in the
school environment and children’s early school adjustment. In
K. Went-
zel & J. Juvonen (Eds.), Social motivation: Understanding
children’s
school adjustment (pp. 199 –225). New York: Cambridge
University
Press.
Blair, C., Granger, D., Kivlighan, K., Mills-Koonce, W. R.,
Willoughby,
M., Greenberg, M. T., et al. (2008). Maternal and child
contributions to
cortisol response to emotional arousal in young children from
low-
income, rural communities. Developmental Psychology, 44,
1095–1109.
Brody, G. H., & Flor, D. L. (1998). Maternal resources,
parenting prac-
tices, and children competence in rural single-parent African
American
families. Child Development, 69, 803– 816.
Bugental, D. B., & Grusec, J. E. (2006). Socialization
processes. In N.
Eisenberg, W. Damon, & R. M. Lerner (Eds.), Handbook of
child
psychology: Social, emotional, and personality development
(6th ed.,
Vol. 3, pp. 366 – 428). Hoboken, NJ: Wiley.
Burchinal, M. R., Campbell, F. A., Bryant, D. M., Wasik, B. H.,
& Ramey,
C. T. (1997). Early intervention and mediating processes in
cognitive

performance of children of low-income, African-American
families.
Child Development, 68, 935–954.
Connor, C. M., & Craig, H. K. (2006). African American
preschoolers’
language, emergent literacy skills, and use of African American
English:
A complex relation. Journal of Speech, Language, and Hearing
Re-
search, 49, 771–792.
Craig, H. K., Connor, C. M., & Washington, J. A. (2003). Early
positive
predictors of later reading comprehension for African American
stu-
dents: A preliminary investigation. Language, Speech, and
Hearing
Services in Schools, 34, 31– 43.
Craig, H. K., Thompson, C. A., Washington, J. A., & Potter, S.
L. (2004).
Performance of elementary-grade African American students on
the
Gray Oral Reading Tests. Language, Speech, and Hearing
Services in
Schools, 35, 141–154.
Culp, A., Hubbs-Tait, L., Cuilp, R., & Starost, H. (2001).
Maternal par-
enting characteristics and school involvement: Predictors of
kindergar-
ten cognitive competence among Head Start children. Journal of
Re-
search in Childhood Education, 15, 5–17.

Dearing, E., McCartney, K., & Taylor, B. A. (2001). Change in
family
income-to needs matters more for children with less. Child
Develop-
ment, 72, 1779 –1793.
Deater-Deckard, K., & Dodge, K. A. (1997). Externalizing
behavior prob-
lems and discipline revisited: Nonlinear effects and variations
by culture,
context, and gender. Psychological Inquiry, 8, 161–175.
Denavas-Walt, C., Proctor, B. D., & Lee, C. H. (2006). Income,
poverty,
and health insurance coverage in the United States. Washington,
DC:
U.S. Census Bureau, U.S. Government Printing Office.
Dodici, J., Draper, D. C., & Peterson, C. A. (2003). Early
parent– child
interaction and early literacy development. Topics in Early
Childhood
Special Education, 23, 124 –136.
Dornbusch, S. M., Ritter, P. L., Leiderman, P. H., Roberts, D.
F., &
Fraleigh, M. J. (1987). The relation of parenting style to
adolescent
performance. Child Development, 58, 1244 –1257.
Duncan, G. J., Brooks-Gunn, J., & Klebanov, J. K. (1994).
Economic
deprivation and early childhood development. Child
Development, 65,
296 –318.

DEVELOPMENT
Egeland, B., & Heister, M. (1995). The long-term consequences
of infant
day-care and mother–infant attachment. Child Development, 66,
474 –
485.
Egeland, B., Pianta, R., & O’Brien, M. A. (1993). Maternal
intrusiveness
in infancy and child maladaptation in early school years.
Development
and Psychopathology, 5, 359 –370.
Elardo, R., Bradley, R., & Caldwell, B. M. (1977). A
longitudinal study of
the relation of infants’ home environment to language
development at
age three. Child Development, 48, 595– 603.
Evans, G. W. (2004). The environment of childhood poverty.
American
Psychologist, 59, 77–92.
Garcia Coll, C. T. (1990). Developmental outcome of minority
infants: A
process-oriented look into our beginnings. Child Development,
61, 270 –
289.
Garcia Coll, C. T., Lamberty, G., Jenkins, R., McAdoo, H. P.,
Crnic, K.,
Wasik, B. H., & Garcia, H. V. (1996). An integrative model for

the study
of developmental competencies in minority children. Child
Develop-
ment, 67, 1891–1914.
Garrett-Peters, P., Mills-Koonce, W. R., Vernon-Feagans, L.,
Willoughby,
M. W., & Cox, M. J. (2008). Predictors of parental emotion
language in
infancy. Parenting: Science and Practice, 8, 117–152.
Hart, B., & Risley, T. R. (1992). American parenting of
language-learning
children: Persisting differences in family– child interaction
observed in
natural home environments. Developmental Psychology, 28,
1096 –
1105.
Hart, B., & Risley, T. R. (1995). Meaningful differences in the
everyday
experiences of young American children. Baltimore, MD: Paul
H.
Brookes.
Heller, T., & Baker, B. (2000). Maternal negativity in children’s
external-
izing behavior. Early Education and Development, 11, 483–
498.
Hirsh-Pasek, K., & Burchinal, M. (2006). Putting language
learning in
context: How changes at home and in school affect language
growth
across time. Merrill-Palmer Quarterly, 52, 449 – 485.

Hoff, E. (2003). The specificity of environment influence:
Socioeconomic
status affects early vocabulary development via maternal
speech. Child
Development, 74, 1368 –1378.
Hoff-Ginsberg, E. (1991). Mother– child conversation in
different social
classes and communicative settings. Child Development, 62,
782–796.
Hox, J. (2002). Multilevel analysis: Techniques and
applications. Mahwah,
NJ: Erlbaum.
Ispa, J. M., Fine, M. A., Halgunseth, L. C., Harper, S.,
Robinson, J., Boyce,
L., et al. (2004). Maternal intrusiveness, maternal warmth, and
mother–
toddler relationship outcomes: Variation across low -income
ethnic ac-
culturation groups. Child Development, 75, 1613–1631.
Johnson, D. L. (2001). The influences of social class and race
on language
test performance and spontaneous speech of preschool children.
Child
Development, 45, 517–521.
Keown, L., Woodward, L., & Field, J. (2001). Language
development of
pre-school children born to teenage mothers. Infant and Child
Develop-
ment, 10(3), 129 –145.
Lawrence, V. W. (1997). Middle- and working-class Black and

White
children’s speech during a picture-labeling task. The Journal of
Genetic
Psychology, 158, 226 –240.
Linver, M. R., Brooks-Gunn, J., & Kohen, D. E. (2002). Family
processes
as pathways from income to young children’s development.
Develop-
mental Psychology, 38, 719 –734.
Little, R. A. A., & Rubin, D. B. (1987). Statistical analysis with
missing
data. New York: Wiley.
Magnuson, K. A., & Duncan, G. J. (2006). The role of family
socioeco-
nomic resources in the Black–White test score gap among young
chil-
dren. Developmental Review, 26, 365–399.
McLoyd, V. C. (1998). Socioeconomic disadvantage and child
develop-
ment. American Psychologist, 53, 185–204.
McLoyd, V. C., & Ceballo, R. (1998). Conceptualizing and
assessing
economic context: Issues in the study of race and child
development. In
V. C. McLoyd & L. Steinberg (Eds.), Studying minority
adolescents:
Conceptual, methodological, and theoretical issues (pp. 251–
278). Mah-
wah, NJ: Erlbaum.

McLoyd, V. C., & Smith, J. (2002). Physical discipline and
behavior
problems in African American, European American, and
Hispanic chil-
dren: Emotional support as a moderator. Journal of Marriage
and the
Family, 64, 40 –53.
Mills-Koonce, W. R., Propper, C., Gariépy, J. L., Blair, C.,
Garrett-Peters,
P., & Cox, M. J. (2007). Bi-directional genetic and
environmental
influence on mother and child behavior: The family system as
the unity
of analyses. Development and Psychopathology, 19, 1073–1087.
Mistry, R. S., Biesanz, J. C., Taylor, L. C., Burchinal, M., &
Cox, M. J.
(2004). Family income and its relation to preschool children’s
adjust-
ment for families in the NICHD Study of Early Child Care.
Develop-
mental Psychology, 40, 717–745.
Mistry, R. S., Melsch, A., & Taheri-Kenaru, A. (2003,
September). As-
sessing the relations among maternal employment, family
processes, and
preschoolers’ cognitive and social adjustment for families in the
Com-
prehensive Child Development Program (CCDP). Paper
presented at
Northwestern University/University of Chicago Joint Center for
Poverty
Research HHS-ASPE/Census Bureau Research Development
Grants

Conference, Chicago.
Murry, V. M., Brown, P. A., Brody, G. H., Cutrona, C. E., &
Simons, R. L.
(2001). Racial discrimination as a moderator of the links among
stress,
maternal psychological functioning and family relationships.
Journal of
Marriage and the Family, 63, 915–926.
Early Child
Care Research Network. (1997). The effects of infant child care
on
infant–mother attachment securing: Results of the NICHD Study
of
Early Child Care. Child Development, 68, 860 – 879.
Early Child
Care Research Network. (2000). The relation of child care to
cognitive
and language development. Child Development, 71, 960 –980.
Early Child
Care Research Network. (2005). Pathways to reading: The role
of
language in the transition to reading. Developmental
Psychology, 41,
428 – 442.
Early Child
Care Research Network. (2006). Infant–mother attachment: Risk
and

protection in relation to changing maternal caregiving quality
over time.
Developmental Psychology, 42, 38 –58.
O’Neill, D. K., Pearce, M. J., & Pick, J. L. (2004). Preschool
children’s
narratives and performance on the Peabody Individualized
Achievement
Test–Revised: Evidence of a relation between early narrative
and later
mathematical ability. First Language, 24, 149 –183.
Pancsofar, N., & Vernon-Feagans, L. (2006). Mother and father
language
input to young children: Contributions to later language
development.
Journal of Applied Developmental Psychology, 27, 571–587.
Parke, R. D., & Buriel, R. (2006). Socialization in the family:
Ethnic and
ecological perspectives. In N. Eisenberg, W. Damon, & R. M.
Lerner
(Eds.), Handbook of child psychology: Social, emotional, and
person-
ality development (6th ed., Vol. 3, pp. 429 –504). Hoboken, NJ:
Wiley.
Peisner-Feinberg, E., Burchinal, M., Clifford, R., Culkin, M.,
Howes, C.,
Kagan, S., & Yazejian, N. (2001). The relation of preschool
child-care
quality to children’s cognitive and social developmental
trajectories
through second grade. Child Development, 72, 1534 –1553.
Pianta, R. C. (1997). Adult– child relationship processes and

early school-
ing. Early Education and Development, 81, 11–26.
Pianta, R. C., Nimetz, S. L., & Bennett, E. (1997). Mother–
child relation-
ships, teacher– child relationships, and school outcomes in
preschool and
kindergarten. Early Childhood Research Quarterly, 12, 263–280.
Pianta, R. C., & Walsh, D. (1996). High-risk children in the
schools:
Creating sustaining relationships. New York: Routledge.
556 PUNGELLO ET AL.
Prelow, H. M., Danoff-Burg, S., Swenson, R. R., & Pugliano, D.
(2004).
The impact of ecological risk and perceived discrimination on
the
psychological adjustment of African American and European
American
youth. Journal of Community Psychology, 32, 375–389.
Propper, C., Willoughby, M., Halpern, C. T., Cox, M., &
Carbone, M. A.
(2007). Parenting quality, DRD4, and the prediction of
externalizing and
internalizing behaviors in early childhood. Developmental
Psychobiol-
ogy, 49, 619 – 632.
Qi, C. H., Kaiser, A. P., Milan, S., & Hancock, T. (2006).
Language
performance of low-income African American children and

European
American children on the PPVT-III. Language, Speech, and
Hearing
Services in Schools, 37, 5–16.
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear
models.
Thousand Oaks, CA: Sage.
Raviv, T., Kessenich, M., & Morrison, F. J. (2004). A
mediational model
of the association between socioeconomic status and three-year-
old
language abilities: The role of parenting factors. Early
Childhood Re-
search Quarterly, 19, 528 –547.
Rubin, K., Burgess, K., Sawyer, K., & Hastings, P. (2003).
Predicting
preschoolers’ externalizing behaviors from toddler
temperament, con-
flict, and maternal negativity. Developmental Psychology, 39,
164 –176.
Scarborough, A. A. (2001). Behavioral patterns of toddlers with
speech
language delay: The relationship with child, family, and poverty
(Doc-
toral dissertation, University of North Carolina at Chapel Hill,
2001).
Dissertation Abstracts International, 61, 4339.
Searle, S. R., Casella, G., & McCulloch, C. E. (1992). Variance
compo-
nents. New York: Wiley.

Shaw, D. S., Winslow, E. B., Owens, E. B., Vondra, J. I., Cohn,
J. E., &
Bell, R. Q. (1998). The development of early externalizing
problems
among children from low-income families: A transformational
perspec-
tive. Journal of Abnormal Child Psychology, 26, 95–107.
Siegel, L. S. (1982). Reproductive, perinatal, and environmental
factors as
predictors of the cognitive and language development of
preterm and
full-term infants. Child Development, 53, 963–973.
Skiba, R. J., Poloni-Staudinger, L., Simmons, A. B., Feggins-
Azziz, L. R.,
& Chung, C. (2005). Unproven links: Can poverty explain
ethnic dis-
proportionality in special education. The Journal of Special
Education,
39, 130 –144.
Snijders, T., & Bosker, R. (1999). Multilevel analysis. London:
Sage.
Stevenson, H. W., & Newman, R. S. (1986). Long-term
prediction of
achievement and attitudes in mathematics and reading. Child
Develop-
ment, 57, 646 – 659.
Storch, S. A., & Whitehurst, G. J. (2002). Oral language and
code-related
precursors to reading: Evidence from longitudinal structural
model.
Developmental Psychology, 38, 934 –947.

Tamis-LeMonda, C. S., Bornstein, M. H., & Baumwell, L.
(2001). Mater-
nal responsiveness and children’s achievement of language
milestones.
Child Development, 72, 748 –767.
Tamis-LeMonda, C. S., Shannon, J. D., Cabrera, N. J., & Lamb,
M. E.
(2004). Fathers and mothers at play with their 2- and 3-year
olds:
Contributions to language and cognitive development. Child
Develop-
ment, 75, 1806 –1820.
Thompson, C. A., Craig, H. K., & Washington, J. A. (2004).
Variable
production of African American English across oracy and
literacy con-
texts. Language, Speech, and Hearing Services in Schools, 35,
269 –282.
Walker, D., Greenwood, C., Hart, B., & Carta, J. (1994).
Prediction of
school outcomes based on early language production and
socioeconomic
factors. Child Development, 65, 606 – 621.
Zimmerman, I. L., Steiner, V. G., & Pond, R. E. (2002). The
Preschool
Language Scale: Fourth Edition, examiner’s manual. San
Antonio, TX:
The Psychological Corporation.
Zimmerman, I. L., Steiner, V. G., & Pond, R. E. (2004). The
Preschool

Language Scale: Fourth Edition. San Antonio, TX: The
Psychological
Corporation.
Received August 2, 2007
Revision received July 10, 2008
Accepted July 29, 2008 �
DEVELOPMENT
The Impact of Poverty and Homelessness on Children’s
Oral and Literate Language: Practical Implications for
Service Delivery
from a presentation at ASHA Schools Conference
Milwaukee, Wisconsin
July 28, 2012
By Celeste Roseberry-McKibbin, PhD
California State University, Sacramento
San Juan Unified School District

I. Key Points
● Statistics regarding poverty in the U.S.
● Factors that impact low-SES students’ linguistic and academic
achievement
● Effects of poverty on oral and literate language development
● Suggestions for supporting low-SES parents in increasing
their children’s language skills
● Strategies for professionals for increasing the oral and written
language skills of low-SES students
● Executive functioning deficits in students and summary of
remediation strategies
II. Understanding Variables Affecting Low-SES Students’
Performance
Background
● Never equate poverty with dysfunction.
● The term, poverty, often brings to mind the cultural
differences that arise from race, ethnicity,
religion, country of origin, and ability or disability. However,
in many countries, substantial cultural
differences exist between people who are economically
disadvantaged and those who are
advantaged (Turnbull & Justice, 2012).

Variables
• The standard of living for those in the bottom 10% is lower in
the United States than in any other
developed nation, except the United Kingdom.
• Poor families with three or more people spend about one third
of their income on food.
• Last year, 7.7% of African American women and 8.5% of
Hispanic women worked in jobs that paid
at or below minimum wage, as compared to 4.3% of White men
(www.nwlc.org, 2011).
• African American and Hispanic women are more likely than
white women to be heads of
households.
• Married households’ median annual 2011 income was $71,830,
while female-headed households
earned $32,597.
Effects of Homelessness
• Homeless children and youth lack a fixed, regular, and
adequate nighttime residence.
• These children often live in cars, parks, public places,
abandoned buildings, or bus or train
stations.
• The cause is the inability of people to pay for housing; thus,
homelessness is impacted by both
income and the affordability of available housing (National

Alliance to End Homelessness, 2012).
Potential Psychological and Physical Effects
• Malnutrition
• Illness
• Hearing and vision problems
• Housing problems (e.g., lead poisoning, homelessness,
frequent moving, crowded conditions, no
place to play outside)
• Neighborhood problems (e.g., violence)
• Family stress
• Fewer learning resources
• Lack of cognitive and linguistic stimulation
Observations
● When financial resources are stressed, there are higher rates
of maternal depression.
● Compared with higher-income mothers, who tend to be more
warm and verbal with their children,
low-income mothers often show lower levels of warmth,
responsiveness, and sensitivity when
interacting with young children. (Barrett & Turner, 2005; La
Paro, Justice, Skibbe, & Plante, 2004;
Neuman, 2009)
● The overall warmth and effect of a home, which promote
caregiver-child bonding, form the very
foundation of language development.
III. Definition of Situational vs. Generational Poverty
(Payne, 2003; Roseberry-McKibbin, 2013)

Characteristics of Situational Poverty
• Common for immigrants
• Occurs for a shorter period of time
• Usually the result of circumstances (divorce, illness, death)
• People have a sense of pride and a belief in their ability to rise
above their circumstances through
hard work.
• They may refuse to accept offers of help as “charity.”
Characteristics of Generational Poverty
• Affects a family for two generations or longer
• Usually involves welfare
• A common attitude is “I am stuck, and the world owes me.”
• There is a short-term value system, which emphasizes survival
in the present—not planning for
the future (e.g., long-range educational plans).
Comparison of Situational and Generational Poverty
The values of persons in situational and generational poverty
may differ in a number of
areas.
SITUATIONAL
• Life priorities include achievement,

possessions, status.
• Money is to be saved, managed, invested.
• Religion is one of the accoutrements of
life; fits into the person’s schedule.
• Time is to be valued; punctuality is
critical; the future is important.
• Destiny is in our hands; we all have
choices; there is an internal locus of
control.
• Education is crucial for getting ahead in
life, making good $$, being respected.
• Entertainment is a reward for hard work;
money is used for education and life
comforts; leftover $$ is used for
entertainment after other priorities are
met.
• Discipline is important; punishment/
negative consequences are about change;

“don’t be sorry, be different.”
• Organization and planning are very
important. Life is carefully scheduled into
structured time slots. Structure is crucial:
Calendars, iPhones, and other
organizational devices proliferate.
• With language, formal register is used;
language is used to meet needs, get ahead
in life.
• Interaction style values quiet;
conversational partners do not interrupt,
but politely wait their turn.
GENERATIONAL
• Survival, entertainment, relationships are
important; it’s all about the PRESENT.
• Money is to be spent, especially on things
that bring pleasure in the moment.
• Religion may be the center of much of life;
a great deal of time may be spent at the
church.

• “You get there when you get there”; the
present is most important;
• “You can’t fight city hall”; there can be
learned helplessness; there is an external
locus of control.
• Education is valued in the abstract, not
emphasized as a real or attainable goal.
• Entertainment plays a crucial role and is
highly valued; it may take precedence over
education; the present is all we have (e.g.,
Why not enjoy life right now?); live in the
moment.
• Punishment is not about change; it is
about penance and forgiveness; the
person’s behavior continues as before.
• Organizational/planning devices are
virtually nonexistent. Clutter is common;
structure is not valued. Planning ahead is
not common; “living by the seat of your
pants” is typical.

• Casual register is used; language is used
for entertainment and for survival.
• There is constant background noise;
interruptions during conversation are
common and expected.
Home Language
• “Those shoes suck.”
• “Gimme that apple.”
• “Dude, that was totally stupid.”
School Language
• “Those shoes are different than your
usual.”
• “I’m hungry—that apple looks good.”
• “Interesting idea—hadn’t thought of it that
way.”
IV. Factors Impacting Oral Language

Language Characteristics Correlated With Low SES
• Being poor does not cause children to have language and
behavioral impairments.
• Never equate poverty with dysfunction.
• However, certain language and behavioral characteristics are
associated with being from a low-
SES background (Nelson, 2010).
Limited Access to Health Care
• This issue can impact language skills.
• If the mother is malnourished during pregnancy, the child’s
brain development can be impacted.
• Children who are often sick miss school.
• If children are sick or hungry, they have difficulty learning; it
is hard for them to concentrate.
• Middle ear infections can impact listening and even written
language (e.g., reading, spelling).
Observations
• There is a strong correlation between adults’ education and
their income levels.
• Long-term welfare dependency is associated with low literacy
skills and lack of a high school
diploma.
• In terms of educational level of caregivers, research has found
that SES is more critical to a child’s
language development than ethnic background.
• The factor most highly related to SES is the mother’s
educational level.
Caretakers Who Have Little Formal Education
• They may not provide adequate oral language stimulation for

children.
• They may not believe that it is important to talk with babies
and young children (who are not
treated as conversational partners).
Research
Pruitt & Oetting (2009)
• Children from low-income families have been shown to have
limited input, in terms of volubility
and quality, when compared to children from wealthier families,
and these differences have been
linked to delayed language abilities.
Nelson (2010)
• Children in low-income families are engaged more in talk
about immediate daily living concerns—
for example, what to eat, wear, and do or not do.
• Conversations in low-SES homes often do not extend beyond
practical concerns.
• One consequence of this is that low-SES children often have
very concrete language.
• They have difficulty understanding the abstract,
decontextualized language of school.
Hart & Risley (1995)
• The researchers conducted longitudinal studies of families
from various ethnic and SES
backgrounds.
• Over several years, they observed behavior in the homes of 1-

to 2-year-old children from three
groups: welfare, working class, and professional.
• Hart and Risley concluded that SES made an “overwhelming
difference” in how much talking went
on in a family.
• The family factor most strongly associated with the amount of
talking in the home was not
ethnicity, but SES.
• In a 365-day year, children from professional families would
have heard 4 million utterances.
• Children from welfare families would have heard 250,000
utterances.
• The number of utterances in working class families fell
somewhere in between.
• Even by 3 years of age, the difference in vocabulary
knowledge between children from welfare
homes and those from middle class homes was so great that—in
order for the welfare children to
gain a vocabulary equivalent to that of children from working
class homes—the welfare children
would need to attend a preschool program for 40 hours per week
where they heard language at a
level used in the homes of professional families..
IV. Strategies to Enhance Language Stimulation in Infants
• Research shows that high-quality preschool programs portend
the best short- and long-term

Discussion Week 4 Possible Effects of Poverty on Young Children’s

Discussion Week 4 Possible Effects of Poverty on Young Children’s

Recommended

Recommended

More Related Content

Similar to Discussion Week 4 Possible Effects of Poverty on Young Children’s

Similar to Discussion Week 4 Possible Effects of Poverty on Young Children’s (20)

More from DustiBuckner14

More from DustiBuckner14 (20)

Recently uploaded

Recently uploaded (20)

Discussion Week 4 Possible Effects of Poverty on Young Children’s