Program Evaluation on Early Head Start

Rossi, P. H., Lipsey, M., & Freeman, H. E. (2004). Evaluation: A Systematic Approach (7 th ed.). Thousand Oaks, CA: Sage.

This is the other source..However, It is a book I think Ive included all the information I need from the book so no need to worry about this part but in the event one may need it here is the source.

Also this is a Policy, Planning, and Budgeting class.

CRIMINAL JUSTICE POLICY, PLANNING, AND EVALUATION

CRIM 5450 (01)

SPRING 2018 – TERM PAPER ONE

Using the Bachman & Schutt (2015) Logic Model provided, write a six (6) page program evaluation paper titled, “How to Evaluate an Early Head Start Program in the United States.” The cover page and reference page are not included in the six pages.

Early Head Start
is a comprehensive program that focuses on enhancing children’s development while providing educational opportunities. In your paper, assume that the Head Start program you are evaluating is designed to provide services to low-income women with infants and toddlers up to three (3) years of age.

The paper, written to APA requirements and double spaced using 12-point
Times New Roman
font, must address the various aspects of program evaluation, as seen from the Logic Model:

Your paper should have the following subsections:

1. Cover page

2. Introduction that provides some information about program evaluation.

3. Program stakeholders: Who are the likely stakeholders for this program?

4. Inputs: What are the inputs needed to successfully evaluate this program? What are the connections between the various inputs?

5. Program process: Describe what the program process will entail to achieve a successful evaluation.

6. What are the outputs of the program?

7. What are the program outcomes?

8. What are the challenges likely to be faced during the evaluation process?

9. Summary: Summarize how all these steps of program evaluation come together to make the program evaluation exercise useful.

10. Reference page: Use between 4 and 6 scholarly sources, including your textbook. Scholarly sources are: peer-reviewed articles, government reports, and textbooks.

The completed paper must be submitted on Blackboard no later than 11:59 pm on February 5, 2018. Please note that your paper will be checked using anti-plagiarism software.

Dr.Daniel K. Pryce

Criminal Justice Policy, Planning, and Evaluation
CRIM 5450 – Term Paper One Grading Rubric

Page 1 of 3

Dimension

Exceeds Expectations

90% and above

Meets Expectations

89%-70%

Does Not Meet Expectations

Below 70%

Introduction to

Evaluation of

the Head Start

program

10 Points

The introduction accurately

describes the evaluation being

undertaken. Description of issue is

strongly based on empirical

knowledge and not folk knowledge

(e.g., things seen on the Internet or

television). Purpose of evaluation is

well articulated.

10 – 9 pts.

The introduction minimally describes

the evaluation being undertaken.

Description of issue is based on

empirical knowledge and not folk

knowledge (e.g., things seen on the

Internet or television). Purpose of

evaluation is minimally articulated.

8.9 – 7 pts.

The introduction poorly describes the

evaluation being undertaken. Description of

issue is not based on empirical knowledge but

on folk knowledge (e.g., things seen on the

Internet or television). Purpose of evaluation

is poorly articulated.

6.9 – 0 pts.

Program

Stakeholders

10 Points

Strong logical connection between

program stakeholders identified.

Detailed, well-articulated research

that properly explains the choice of

stakeholders. Scholarly sources are

clearly used to support the choice of

stakeholders.

10 – 9 pts.

Weak logical connection between

program stakeholders identified.
Detailed, well-articulated research
that properly explains the choice of
stakeholders. Scholarly sources are

minimally used to support the choice

of stakeholders.

8.9 – 7 pts.

No logical connection between program

stakeholders identified. Inadequately

articulated research that explains the choice

of stakeholders. Scholarly sources are poorly

used to support the choice of stakeholders.

6.9 – 0 pts.

Inputs

10 Points
Strong logical connection between

program inputs. Detailed, well-

articulated research that properly

explains the choice of inputs.

Scholarly sources are clearly used to

support the choice

of inputs.

10 – 9 pts.
Weak logical connection between
program inputs. Detailed, well-
articulated research that properly
explains the choice of inputs.

Scholarly sources are minimally used

to support the choice of inputs.

8.9 – 7 pts.
No logical connection between program

inputs. Inadequately articulated research that

explains the choice of inputs. Scholarly

sources are poorly used to support the choice

of inputs.

6.9 – 0 pts.

Dr. Daniel K. Pryce

Criminal Justice Policy, Planning, and Evaluation
CRIM 5450 – Term Paper One Grading Rubric

Page 2 of 3

Program

Process

10 Points

A clear and research-supported

description of the program

evaluation process. An accurate

description of the steps in the

program development process.

10 – 9 pts.

An imprecise, but research-

supported, description of the program

evaluation process. A minimally

correct description of the steps in the

program development process.
8.9 – 7 pts.

A poor description of the program process

that is also not undergirded by research. A

poor description of the steps in the program

development process.

6.9 – 0 pts.
Program

Outputs

10 Points
Strong logical connection between

program outputs. Detailed, well-

articulated research that properly

explains why you reached the

particular choice of outputs.

Scholarly sources are clearly used to

support the choice of outputs.

10 – 9 pts.
Weak logical connection between
program outputs. Detailed, well-
articulated research that properly
explains why you reached the
particular choice of outputs.
Scholarly sources are minimally used

to support the choice of outputs.

8.9 – 7 pts.
No logical connection between program

outputs. Inadequately articulated research that

explains why you reached the particular

choice of outputs. Scholarly sources are

poorly used to support the choice of outputs.

6.9 – 0 pts.
Program

Outcomes

10 Points
Strong logical connection between

program outcomes. Detailed, well-

articulated research that properly
explains why you reached the

particular choice of outcomes.

Demonstrates a clear understanding

of the difference between outputs

and outcomes.

10 – 9 pts.
Weak logical connection between
program outcomes. Detailed, well-
articulated research that properly
explains why you reached the
particular choice of outcomes.

Demonstrates some understanding of

the difference between outputs and

outcomes.

8.9 – 7 pts.
No logical connection between program

outcomes. Inadequately articulated research

that explains why you reached the particular

choice of outcomes. Demonstrates a poor

understanding of the differences between

outputs and outcomes.

6.9 – 0 pts.

Dr. Daniel K. Pryce
Criminal Justice Policy, Planning, and Evaluation
CRIM 5450 – Term Paper One Grading Rubric

Page 3 of 3

Challenges and

Summary of

Program

Evaluation

20 points

Provides a detailed explanation of

the challenges to be expected

during the program evaluation

process. Provides a clear and

detailed summary of how the

various stages of the program

evaluation come together to form

the whole.

20 – 18 pts.

Provides some explanation of the

challenges to be expected during the

program evaluation process. Provides a

summary of how the various stages of

the program evaluation come together

to form the whole.

17.9 – 14 pts.

Provides a poor explanation of the

challenges to be expected during the
program evaluation process. Provides a

poor summary of how the various stages

of the program evaluation come together

to form the whole.

13.9 – 0 pts.

Sources and APA

10 Points

Paper properly uses 4 or more

sources to support arguments and

the evaluation of the Head Start

program. All sources are peer

reviewed. APA guide is strictly

followed (e.g., proper use of in-text

citations and correct format for

accompanying references).

10 – 9 pts

Paper properly uses 3 or more sources

to support arguments and the

evaluation of the Head Start program.

All sources are peer reviewed. Minor

(few) departures from APA guide (e.g.,

minor mistakes in use of in-text

citations and partially correct format

for accompanying references).

8.9 – 7 pts

Paper properly uses fewer than 3

sources to support arguments and the

evaluation of the Head Start program.

Some sources are not peer reviewed.

Significant (several) departures from

APA guide (e.g., major mistakes in use

of in-text citations and incorrect format

for accompanying references).

6.9 – 0 pts

Writing

10 Points

Paper is coherently organized, and

the logic is easy to follow. There

are no spelling or grammatical

errors and terminology is clearly

defined. Writing is clear, concise,

and

persuasive.

10 – 9 pts

Paper is somewhat organized, and the

logic is easy to follow. There are few

spelling or grammatical errors and

terminology is clearly defined. Writing

is somewhat clear, concise, and

persuasive.

8.9 – 7 pts

Paper is disorganized and/or the logic is

difficult to follow. There are several

spelling or grammatical errors and

terminology is unclear. Writing is not

clear or comprehensible.

6.9 – 0 pts

BACKGROUND LITERATURE REVIEW

PERTAINING TO THE
EARLY HEAD START STUDY

HelenH.Raikes, JeanneBrooks-Gunn,and JohnM.Love

Although considerable information exists about the effects of early
interventions for at-risk children, we know more about intervention effects
and results of investments in programs for children of specific ages, for
example, 3- to 5-year-olds, than about when to invest or for whom specific
investments are most advantageous across the age span from birth to 5.
Outside of a few program evaluations that span the period from birth to age

(Garber & Heber,

1; Ramey & Campbell, 198

; St. Pierre, Goodson,
Layzer, & Bernstein, 1994), little is known about cumulative intervention
experiences during the period from birth until formal schooling begins.
Moreover, variations in program models and timing of services have not been
examined. Investigation of the variability in quantity and timing of services
over the years from birth to age 5, the focus of this monograph, is likely to be
useful to programs for fine-tuning the timing and intensity of interventions,
to policy makers for optimizing early childhood investments, and to
developmental scientists for better understanding trajectories of develop-
ment especially of poor children in the context of environmental influences.

This monograph reports on a program evaluation of 3,001 children in 1

sites from poor families, half of whom were randomized to receive Early Head
Start (EHS) services in the first 3 years of life (for some families in some sites
EHS services began prenatally; ACF,

002a; Love et al., 2005), and half of
whom were not. Children’s outcomes were examined at ages 2 and 3 when
concurrent impacts of the EHS programs could be examined, and at age 5, 2
years after EHS ended and when formal program experiences subsequent to
EHS could be examined. Analysis of program impacts for families and
children in the first 5 years of life are based on an experimental evaluation.
However, looking at the services that families obtained for their children in

Corresponding author: Helen Raikes, Child, Youth and Family Studies, 257 Mabel Lee
Hall, University of Nebraska-Lincoln, Lincoln, Nebraska

8588-0236, email: hraikes2@unl.
edu

the preschool years allows for a description of how combinations of infant
and toddler (for children from birth to age 3) and preschool (for 3- to 5-year-
old children) services may influence school readiness in low-income
children.1 Thus, the monograph addresses both longitudinal treatment
impacts, as well as longitudinal variations in experience and associated
outcomes.

The advantages of early intervention programs for vulnerable children
prior to school entry are generally acknowledged (Barnett, 2011; Camilli et al.,
20

; Duncan & Magnuson, 2006). Although programs may have multiple
purposes, most ultimately aim to reduce gaps in school readiness between low-
income and more advantaged children. Low-income children typically enter
school from half to a full standard deviation below more advantaged children
in academic-related domains such as vocabulary, cognition, and specific
literacy-related skills, and often demonstrate challenges in social–emotional
and regulatory functioning (Brooks-Gunn & Duncan, 1997; Duncan &
Magnuson, 2005; Hart & Risley, 1995; Reardon & Galindo, 2009; Rouse,
Brooks-Gunn, & McLanahan, 2005; Stipek & Ryan, 1997). Moreover, many of
these gaps are observable much before school entry, as early as age

(Klebanov, Brooks-Gunn, McCarton, & McCormick, 1998) and possibly in the
toddler years. Differences in children’s environments during the earliest years
have been linked to school-age outcomes, typically operating through links
with early outcomes (Duncan, Brooks-Gunn, & Klebanov, 1994; Hart &
Risley, 1995). Several notable studies document that low-income children
receive less cognitive and linguistic stimulation than do children in higher-
income families (Bradley et al., 1989; Brooks-Gunn & Markman, 2005;
Klebanov et al., 1998; Zill, 1999). For example, low-income children receive
about a fifth of the language inputs from parents that more-advantaged
children receive (Hart & Risley, 1995).

Children who receive high-quality intervention services, compared to
children who do not receive these services, enter school with greater skills in
school-success domains (Barnett, 2011; Karoly, Kilburn & Cannon, 2005;
Ramey & Ramey, 2006; Schweinhart, 2006), and continue on relatively higher
success trajectories at least through elementary school (Camilli, Vargas, Ryan,
& Barnett, 2010; Heckman, 2006). As a consequence, many states now invest
in prekindergarten programs and/or services for younger children (Barnett,
et al., 2006). Policy makers agree that high-quality early childhood services for
low-income children are valuable (Brooks-Gunn, 2011; Gormley, 2011).
However, most evaluations have examined effects of a single program (Olds et
al., 1997; Ramey & Ramey, 2006) or for a discrete portion of the preschool
years (e.g., Schweinhart, 2006). Investigations of relative and cumulative
contributions of combinations of program services from birth to age 5 have
been limited, although it has been recommended that comprehensive and
systematic assessment of early childhood experiences over time would be

more productive than relying on investigations of brief or one-time programs
(e.g., Reynolds, Wang, & Walberg, 2003).

In this monograph, we present findings from multiple analyses from the
Early Head Start Research and Evaluation Project (EHSREP) that tell a story
about when and how intervention experiences throughout the period birth to
age 5 may have contributed to the outcomes for poor children at school entry.
Outcomes are examined for children who were randomly assigned before age
1 into EHS or a control group and followed through age 5 (shortly before they
began kindergarten). Specifically, in this monograph, we (1) examine the
patterns of impacts of EHS on children ages 2, 3, and 5, emphasizing age 5
impacts measured 2 years after the program ended; (2) report on children’s
formal program experiences after EHS and examine the impact of EHS
on the probability of children receiving follow-up program experiences;
(3) report on the influences of formal preschool programs on age 5 outcomes
above and beyond the effects of EHS; and (4) consider how various patterns of
early experiences from birth to age 5 are associated with the observed
prekindergarten outcomes. A formal preschool program is defined as a
center-based program that may include child care, prekindergarten, or Head
Start.2 We present each of the findings for selected subgroups of children and
families, examining variations according to race/ethnicity (African Ameri-
can, Hispanic, or White), and level of cumulative family demographic risk
(summing across whether mother was a teenager at the time child’s birth,
unemployed or not in school, unmarried, receiving TANF/AFDC, and not a
high school graduate at the time the study began). We also examine three
EHS program models (comparing infant and toddler experiences that were
initially center-based, home-based/home-visiting, or a combination of these).
The monograph addresses these questions using several design and analytic
approaches including experimental and nonexperimental regressions as well
as more exploratory, descriptive approaches. Although confidence in
inferring conclusions varies as a result of these different approaches, the
several questions, linked by an overarching conceptual framework, provide
fertile ground for more comprehensive ways of thinking about children’s
early development in the context of poverty and early childhood intervention
programs than has been typical in the literature to date.

This literature review begins the monograph by laying out the theoretical
foundation for the work, and it surveys what is known about the prevalence of
formal program participation prior to school entry and the effects of
intervention programs. We also provide an overview of the EHS program.
Next, we provide an overview of the service context for low-income children
birth to age 5; examine outcomes from programs for children targeting
infants and toddlers, preschoolers, or children from birth to age 5; and
examine extant research that pertains to subgroups of children of interest in
this monograph. These subgroups are defined by race/ethnicity and level of

3
BACKGROUND LITERATURE REVIEW

cumulative demographic risk factors. We also examine the impacts for
families enrolled in different program models.

THEORETICAL FRAMEWORK

Our work is informed by a developmental perspective that suggests
interventions are likely to change the slope of developmental trajectories and
that differential experiences of children during various periods may influence
different aspects of child well-being (“principle of developmental timing”
proposed by Ramey & Ramey, 1998). This principle leads us to expect (1) that
parents will be most affected by parenting services during the infant and
toddler years when they are forming their expectations of the child and for
their own parenting; (2) that intervention effects for the parent-child
relationship and social–emotional development will be greatest during the
period of relationship and attachment formation; and (3) that intervention
effects for children will be greatest during periods of most rapid learning in
specific developmental areas. For example, language will be most affected
during periods of rapid language learning; and school-like tasks will be most
affected by periods close to school entry. Our thinking has been guided by a
perspective suggesting that concurrent intervention effects are most likely
to influence readiness in the first 5 years. However, we have been further
informed by alternative views about timing of intervention effects. Few research
teams have considered the additive or interactive effects of intervention and
time. We acknowledge the relative newness and potentially post hoc nature of
this way of thinking currently; however, we also note the soundness of the basic
principles, the importance of questions about the most effective timing of
intervention for different forms of development, and challenge the field to
further develop time by intervention hypotheses to guide studies in the future.

The NICHD Early Child Care Research Network (NICHD ECCRN, 2001)
has proposed four alternative explanations or hypotheses for how the timing
of experiences may influence development: (1) The hypothesis of
Experiences at Specific Points in Development posits that interventions will
have more value when timed to coincide with sensitive periods in children’s
development, for example, we might expect that providing responsive
parenting during the first year of life might be most important for subsequent
relationships; (2) the Early Experiences hypothesis suggests that early
experiences will outweigh later ones; consistent with this hypothesis, we would
expect some effects from EHS to outweigh those of later prekindergarten
experiences because of the former’s primacy in setting trajectories, as might
be the case for social and emotional development; (3) the Contemporaneous
Experiences hypothesis posits that current experiences may be more
important than earlier ones; here, we might expect prekindergarten

education to matter more than earlier services vis-à-vis school readiness; (4)
the hypothesis of Incremental or Augmented Experiences suggests that early
experiences produce effects that are maintained by later experiences. We
might expect children who received EHS together with preschool education
to be better prepared for school than children who did not receive it.

Certainly, developmental processes are amplified by transactional
processes (Sameroff & Fiese, 2000), by which children’s development and
experiences at one point in time contribute to experiences that children
receive subsequently. This way of thinking is consistent with that of Heckman
and Masterov (2004), who suggest that “more begets more.” Children who
have more skills attract more experiences subsequently. However, little is
known about the relative contributions of “early” (e.g., 0–3) and “later” (e.g.,
3–5) experiences to later development.

In their conceptual approach to early childhood intervention, Ramey and
Ramey (1998) postulate that intensity, directness, breadth, and flexibility of
program experiences maximize opportunities for children at risk. However,
precisely when to target intervention within the first 5 years of life, which is
generally a time of rapid development, and how to vary intensity and breadth
and for different subgroups has yet to be explicated. Moreover, as stated by
the Rameys’ “principle of environmental maintenance of development”
(p. 117), adequate supports must be in place to maintain children’s positive
gains after programs end. The current study investigates variability in timing
and type of intervention for children with differing characteristics.
Particularly, our study investigates variability in supportive early childhood
experiences in the two years following the 3 years of EHS intervention.

Heckman’s (2006) analyses of early childhood provide continued support
for the notion that early learning influences later learning. One set of analyses
(Cunha, Heckman, Lochner, & Masterov, 2006) suggests that cognitive
processes not only relate to later school success but are particularly amenable
to early intervention whereas social and emotional processes seem to respond
to later intervention. However, these researchers did not have the opportunity
to examine social and emotional processes as early in life as we did (i.e., before
3 years of age), an investigation worth making given the importance of this
early period for attachment and self-regulation. The current study provides an
opportunity to investigate whether specific aspects of development are more
amenable to early (0–3) invention and whether other aspects of development
may be more amenable to later (3–5) intervention.

THE EARLY HEAD START PROGRAM

We begin by providing background on the EHS program, on the
EHSREP, and on general findings when the program ended; this monograph

5
BACKGROUND LITERATURE REVIEW

emphasizes children’s experiences after EHS, during the period when
children were 3–5, and child and parent outcomes just prior to children’s
entry into kindergarten as well as describing earlier treatment impacts (at ages
2 and 3) to illustrate patterns of program impacts over time. The 3,001 children
and families in the EHSREP enrolled in one of the 17 EHS programs chosen
to participate in the study (the first 68 EHS programs were funded in fall
1995). These 17 communities were reflective of all EHS sites at the time in
geographic and family diversity.

The EHS program was created through the reauthorization of the Head
Start Act in 1994 and was expanded in 1998. EHS is a Head Start (HS)
program and, as is true for all HS programs, must serve at least 90% families at
the federal poverty level or below, must implement additional criteria so that
children in families with greatest needs in communities are served, and must
recruit at least 10% children with disabilities. EHS programs can begin
services during pregnancy and continue to serve children and families until
children reach age 3. All HS programs are two-generation, providing services
for both children and parents, although many parent services may be referred
to community organizations. At the time of the evaluation, up to 10% of the
national HS budget could be allocated for EHS services. In 2009, the program
served about 70,000 families in 65 communities. However, EHS received $1.1
billion under the American Recovery and Reinvestment Act of 2009, and in
2010 began to serve an additional 55,000 children.

EHS programs conduct community needs assessments to determine the
most appropriate of four specific service delivery models for families: center-
based, home-based, combination, or locally designed options. For purposes of
the research, sites were classified as to whether they were offering home-
based, center-based, or mixed services (a combination of home-based and
center-based services). Program protocols for services to families were
established by the Head Start Program Performance Standards (U.S.
Department of Health and Human Services [DHHS], 1996). Requirements
for each program model are specified (e.g., curriculum, educational
requirements for teachers, group sizes, frequency and length of home visits,
health and developmental screening) and programs are monitored every 3
years for their adherence to the Program Performance Standards. The
Program Performance Standards are undergirded by the Report of the
Advisory Committee on Services for Infants and Toddlers (US DHHS, 1994),
the committee that designed EHS.

The authorizing Head Start Act required evaluation of EHS and,
therefore, an evaluation was launched at the same time the program began.
Because the program was new, an extensive implementation study was
conducted as well. A national contractor was selected (Mathematica Policy
Research, Princeton, NJ, together with Columbia University’s National Center
on Children and Families), and local researchers in 15 universities partnered

with sites to collect data and to pursue specific local questions. They formed a
research consortium with the contractors and ACF. Using the experimental
design, analyses compared program and control groups when children were
2 years old and when they were 3 years old and their enrollment in the
program had ended. EHS services end when children reach age 3. What
expectations were there for children’s education experiences from the time
they left EHS until they entered kindergarten? As noted, the Advisory
Committee on Services to Families with Infants and Toddlers (U.S. DHHS,
1994) specified that EHS programs “transition” their 3-year-old children into
community formal care and education when the EHS program services
ended. The Advisory Committee did not expect impacts to be maintained if
children did not have subsequent early childhood education experiences. In
the next section of this literature review, we first examine the prevalence of
formal programs for children 3–5 (and the likelihood that the vision of the
Advisory Committee for post-EHS experiences could be achieved) and then
report on child and parent outcomes from various combinations of program
experiences for children from 0 to 3, 3 to 5, and 0 to 5.

PREVALENCE OF PARTICIPATION IN FORMAL CARE AND EDUCATION

Although we tracked children’s experiences after EHS into formal
programs when they were 3–5 years of age, it is important to know what would
have been available to them. What was the prevalence of the types of follow-up
experiences the Advisory Committee sought for EHS children? Low-income
children may be served in multiple community settings, with services that vary
in intensity, breadth, and scope. Of particular interest were formal preschool
programs as emphasized by the Advisory Committee (primarily center-based
services that included a structured early childhood program). National
prevalence statistics provide a context for the types of care and education that
could have been available for children starting at age 3. Next we present data
on the prevalence of formal programs for 3- to 5-year-olds, and for specific
types of formal programs (e.g., HS, child care, prekindergarten) during the
period (early 2000s) when follow-up data were collected.

Data from the Early Childhood Longitudinal Study-Kindergarten Cohort
(ECLS-K), which studied a nationally representative sample of children who
attended kindergarten in the fall of 1998, showed that 68% of children
attended structured early childhood education programs (prekindergarten,
Head Start, or center-based child care) during the year before kindergarten
(Rosenthal, Rathbun, & West, 2005). Attendance figures were about 10%
lower for disadvantaged children (58%; Reynolds, Magnuson, & Ou, 2006).
Similarly, data from the National Household Survey of Education Programs
show that 66% of 4-year-olds and 43% of 3-year-olds were in center-based care

7
BACKGROUND LITERATURE REVIEW

and educational settings in 2001 (Mulligan, Brimhall, & West, 2005), and in
2005, 55% of 3- to 5-year-olds were in a center-based program (basically the
average of 3- and 4-year-olds since most 5-year-olds are in kindergarten; Iruka
& Carver, 2006). These included three common forms of formal care and
education—prekindergarten, Head Start, and center-based child care.

Prekindergarten programs provide increasing opportunities particularly
for 4-year-olds. State funding for prekindergarten has grown in the past 10–
15 years although the rate of growth has recently slowed. In 2001–2002, about
the time EHSREP sample children were in or completing preschool, 40 states
served about 700,000 children, mostly 3- and 4-year-olds, including both
general and special education, with state spending of about $2.4 billion. Nine
years later these figures about doubled: in 2010–2011, 39 states served 1.3
million children, at a total cost of $5.5 billion. (Barnett, Robin, Hustedt, &
Schulman, 2003; Barnett, Carolan, Fitzgerald, & Squires, 2011). Many state
programs target low-income children, but in some states preschool services
are nearly universally available, typically for 4-year-olds. Most prekindergarten
programs do not serve children under age 3, although there are exceptions.

HS provides services primarily to 3- and 4-year-old children from the lowest-
income families, those living at or below the federal poverty line, particularly.
With a federal budget of $7.6 billion in 2011, HS served 942,354 children in
2011 and 9

,345 in 2001–2002 (Schmit, 2012b), 90% of whom were at the
federal poverty level or below. Of these, the vast majority, 90%, were age 3 and
older. EHS, serving children under age 3, drew 17.6% of the federal HS
appropriation and served an additional

5,522 children and pregnant women
nationally (Schmit, 2012a). (EHS services were recently expanded to these
numbers by a one-time funding increase through the American Recovery and
Reinvestment Act of 2009.) HS is believed to serve between 40% and 50% of the
eligible children living in poverty in the United States; however, state-sponsored
prekindergarten programs (in some states HS and state prekindergarten
programs may be combined) also serve children eligible for HS. The smaller
EHS program, even with expansion, serves only a small proportion of eligible
infants and toddlers, approximately 3%.

Child care programs (including center-based and home-based programs)
serve large numbers of children beginning when children are infants. In 2002,
data from the nationally representative National Survey of America’s Families
(NSAF) showed that more than 68% of children younger than 5 with low-
income, employed mothers were in some form of nonparental care
(Capizzano & Adams, 2003). The authors reported that 25% of these
children were in center-based child care, an option more commonly used for
3- and 4-year-olds than for younger children. Other prevalent forms of out-of-
home care were relative care (30%), family child care homes (11%), and
nonrelative in-home care (4%). Federal contributions to child care in 2005,
mostly for low-income children, were approximately $5.3 billion (Child Care

Bureau, 2006a); states added at least $2.2 billion in maintenance of effort
funds (Child Care Bureau, 2006b) and TANF transfers and other funds
further contributed. About 1.8 million children were served by federal/state
subsidy child care programs (Child Care Bureau, 2006a).

The foregoing are the common forms of formal programs. In this
monograph, formal program settings (i.e., preschool education) for children
aged 3–5 years were the focus.3 Altogether, several million children living in
low-income families are served in various combinations of formal programs
when children are 3–5 years of age (HS, prekindergarten, and child care). Yet,
as is clear from this brief review, more formal program services tend to be
available for 4-year-olds than for 3-year-olds. EHS programs were charged with
placing children in quality formal care and education through their
remaining preschool years. It is important to determine if services were
available and whether it was possible to meet that goal.

Moreover, early childhood educational services represent billions of
dollars in state and federal investments and time spent in these programs
constitutes substantial proportions of children’s early years. As we will
demonstrate later, many of these programs intend to influence children’s
development and, in the case of those serving poor children, to help reduce
the gaps in school readiness skills.

Children’s access to preschool education programs could vary by
community context (e.g., whether communities are in rural or urban areas
and whether there are good quality formal programs available in a community
for low-income children aged 3–5), family race/ethnicity, family risk factors,
and EHS program model. Anecdotally, it is well known that variability exits in
access to quality early childhood programs across communities. The striking
differences in access to prekindergarten programs for 4-year-olds versus for
3-year-olds (Barnett, Hustedt, Hawkinson, & Robin, 2006), and the greater
number of 4-year-olds than 3-year olds served in HS—in 2002–2003, 53% of
HS children were 4 years old and 34% were 3; the rest were 5 or under 3 years
of age (Early Childhood Learning and Knowledge Center, 2004)—suggest
that some communities might not have services to carry out the EHS vision of
quality preschool follow-up services. For example, studies also show that
children are more likely to have been in center-based care during the year
prior to kindergarten in urban areas than in rural areas. Among African
American children entering kindergarten (in most U.S. states when children
enter kindergarten they must be age 5, although some may be as old as 6),
those in urban areas were more likely to have been in center-based care the
year prior to kindergarten (37%) than those in rural areas (

%); 55% of
urban White children had been in center care the year before kindergarten as
compared to 35.3% of rural White children (Grace et al., 2006). On the other
hand, the same study showed that children were more likely to have been in
HS if they were rural (17% of all rural children in the kindergarten sample)

BACKGROUND LITERATURE REVIEW

versus urban (8.7%). Additionally, 37% of rural African American children
attended HS the year before kindergarten versus 20% of urban African
American children.

Not only are disparities seen within racial groups according to urbanicity;
they are seen between racial/ethnic groups. Low-income African American
children tend to be more likely to use center-based care than are other low-
income children, and Hispanic children tend to be least likely to use this
form of care (Capizzano, Adams, & Ost, 2007; Magnusson & Waldfogel,
2005). Though studies examining formal program use by cumulating family
demographic risk factors do not exist, prekindergarten programs serve
children across a wider socio-economic range than does Head Start. However,
one of the variables that comprises the risk index used in the current
monograph—mother’s education—is known to be associated with program
participation. In one study, children were more likely to enroll in preschool if
their mothers had a graduate or professional degree (66% in at least one
weekly care arrangement) than if they had a high school diploma or GED
(55%) or had not completed high school (35%; Iruka & Carver, 2006).4 We
found no studies examining availability of programs for children ages 3–5
related to types of program services children had received during the
preceding three years, a matter we will pursue in the current study. In general,
the variability in differential supply and access is an issue for the field of early
childhood education (Burchinal, Nelson, Carlson, & Brooks-Gunn, 2008).

IMPACTS OF INTERVENTION PROGRAMS OFFERING SERVICES PRENATAL
TO AGE 3

Since the 1960s, a number of programs have provided intervention
services for children from birth (or prior to birth), during infancy, and in
some cases up to age 3. The programs we consider first do not provide follow-
up services after age 3. During the infant and toddler years, the programs
frequently offer two-generation services to both children and parents. Here,
we review outcomes for children and parents from the Infant Health and
Development Program (Brooks-Gunn, Klebanov, Liaw, & Spiker, 1993; Infant
Health and Development Program [IHDP], 1990; McCarton et al., 1997;
McCormick et al., 2006); the Parent Child Development Centers (PCDCs;
Johnson & Blumenthal, 1985); the Yale Child Welfare program (Seitz,
Rosenbaum, & Apfel, 1985); Healthy Families America (HFA; Daro &
Harding, 1999); Nurse Family Partnership (NFP; Olds et al., 1997; Olds,
Henderson, Kitzman, & Cole, 1995), UCLA Home Visiting/Mother Infant
Group Intervention (Heinicke, Fineman, Rodning, Recchia, & Guthrie,
2001), and Parents as Teachers (PAT: Wagner & Clayton, 1999). Services
these programs offered during the infant and toddler years were home-based,

center-based, or a combination (Howard & Brooks-Gunn, 2009; Sweet &
Appelbaum, 2004). For example, IHDP offered home visits early after infants’
discharge from the hospital; at age 1, children began center-based care as well.

Intervention effects have been reported at age 2 or 3 (when the programs
ended) from participation in intensive infant/toddler programs. Favorable
effects of intervention were found (1) for children’s cognitive development in
the IHDP (IHDP, 1990; Brooks-Gunn et al., 1993) and the Houston PCDC
(Johnson & Blumenthal, 1985); (2) on language development in the IHDP
(Brooks-Gunn et al., 1993) and Yale Child Welfare participants (Seitz &
Provence, 1990); and (3) on social and emotional development among
treatment groups in the IHDP (Brooks-Gunn et al., 1993; IHDP, 1990).
Overall effect sizes in these studies ranged from small to large. Few home
visiting programs studied using rigorous experimental design have demon-
strated positive impacts on child outcomes at or before age 3 across their
entire sample (Howard & Brooks-Gunn, 2009; Sweet & Appelbaum, 2004).

Many infant and toddler programs offer parenting support; most of these
are home visiting programs and a number of them have reported positive
effects for parents (see Howard & Brooks-Gunn, 2009, for a recent review).
Home visiting programs have reported improvements in maternal mental
health and reduced subsequent pregnancies (Kitzman, Cole, Yoos, & Olds,
1997), increased parental reading to children (Johnson, Howell, & Molloy,
1993), greater reliance on nonviolent discipline (Heinicke et al., 2001),
increased sensitivity in interactions (Olds et al., 2002), reduced depressive
symptoms (Gelfand, Teti, Seiner, & Jameson, 1996), and less child
maltreatment (Daro & Harding, 1999; Olds et al., 1997; Olds et al., 1995;
Wagner & Clayton, 1999). Programs that affect parenting have been criticized
because these changes in parents have not been consistently linked to
changes in children’s development (Duncan & Magnuson, 2006, Howard &
Brooks-Gunn, 2009). However, Olds and colleagues have demonstrated
longer term favorable child outcomes following early gains in parent-related
behaviors (Olds, 2006) using impact analyses at multiple points in time.

Of particular relevance is that some of these evaluations have followed
their children through the elementary school years and, in some cases, even
longer. Positive effects attributable to services received during the infant and
toddler years were found on vocabulary test scores in the Yale Child Welfare
Study (Seitz & Provence, 1990), on standardized Iowa Basic Skills test scores
among boys in the Houston PCDC (Johnson & Blumenthal, 1985), and on IQ,
reading, and math achievement in heavier low-birth-weight infants in IHDP
(McCarton et al., 1997) at age 8. Achievement scores were higher at age

in
the IHDP-treated group (McCormick et al., 2006). Long-term effects of the
Yale Child Welfare study also included reduced behavior problems for boys at
age 8 (Seitz et al., 1985) and reduced need for remedial and support services
(Zigler, Taussig, & Black, 1992). The Nurse Family Partnership study found

BACKGROUND LITERATURE REVIEW

fewer arrests, convictions, and probation violations among intervention
participants during adolescence (Olds, 2006). Effect sizes from these
evaluations range from small to moderate, although Hill, Brooks-Gunn,
and Waldfogel (2003) report a dosage effect with large effect sizes on
cognitive development at age 8 among children who experienced more than
350 days of center-based care in the IHDP study over 2 years.

IMPACTS OF PROGRAMS SERVING PREKINDERGARTEN CHILDREN, AGES 3–5

Programs focused specifically on the prekindergarten period (ages 3 and
4, but most typically for 4-year-olds), have an extensive history. These
programs typically include center-based experiences for young children, and
some include comprehensive services for parents, although the parent
component tends to be less prevalent than in programs serving children
under age 3. Fewer programs exclusively target parents of children 3–5 years
of age but rather most tend to focus more directly on children.

Some notable evaluations of preschool programs include those of the
Perry Preschool Program (Schweinhart, 2006); Chicago Child-Parent
Program (Reynolds & Temple, 2006); Tulsa Prekindergarten Program
(Gormley, Gayer, Phillips, & Dawson, 2005); five state-sponsored prekinder-
garten programs in Michigan, New Jersey, Oklahoma, South Carolina, and
West Virginia (Barnett, Lamy, & Jung, 2005), and Head Start (US DHHS,
2005).

A recent meta-analysis identifies 123 experimental or quasi-experimental
evaluations (Camilli et al., 2010). Early childhood programs have short-term
effects on children’s cognitive development and on specific school readiness
measures such as reading. Effect sizes have often been notable, ranging from
0.2 (US DHHS, 2005) to 0.6 (ACF, 2006; Camilli et al., 2010; Reynolds &
Temple, 2006). Short-term school-related achievement gains are possible,
with some evidence pointing to the importance of direct instruction (Barnett,
2011).

Those evaluations that have followed children into later years suggest that
children receiving early childhood education are less likely to be held back in
school or to receive special education services (Camilli et al., 2010). Notable
too are findings showing that treatment children are more likely to finish high
school, less likely to engage in crime, and more likely to be productively
engaged throughout adulthood (Reynolds & Temple, 2006; Schweinhart,
2006). Larger, publically funded programs also have shown evidence of
success, most notably the evaluations of prekindergarten programs (Barnett
et al., 2005; Gormley et al., 2005).

With regard to HS, the HS Impact Study found few lasting effects through
1st grade, although effects were maintained for some subgroups, most notably

African American children (ACF, 2010). Other nonexperimental research
designs have been used to examine effects of HS. Using a sibling design,
Garces, Thomas, and Currie (2002) found that White children who had
attended HS showed a significantly greater likelihood of completing high
school and attending college, as well as some evidence of higher earnings in
early adulthood. African Americans who were former HS participants were
significantly less likely to have been charged or convicted of a crime. Ludwig
and Miller (2006), using a regression discontinuity design, also found
evidence of increased high school graduation rates and postsecondary
participation, irrespective of race/ethnicity, in poor counties with enhanced
HS participation. And, using propensity score matching procedures,
preschool children who attended HS have been compared to those receiving
prekindergarten, other center-based care, noncenter-based care, and
parental care, with school readiness scores being higher for children
attending HS compared to parental or noncenter-based care, but being
similar or lower for children attending prekindergarten programs (Zhai,
Brooks-Gunn, & Waldfogel, 2011; Zhai, Brooks-Gunn, & Waldfogel, 2011).
The largest effects for IHDP were found when comparing children who
received the treatment with those in parental or noncenter-based care (Hill,
Waldfogel, & Brooks-Gunn, 2002). Using nonexperimental data from FACES,
2 years of HS was shown to confer more benefits than 1 year (Wen, Leow,
Hahs-Vaughn, Korfmacher, & Mancus, 2011).

IMPACTS OF PROGRAMS BIRTH TO SCHOOL ENTRY

Studies that focus on services from birth to age 5 are more limited. These
programs are likely to be quite expensive to implement and so it is perhaps
not surprising that their prevalence is not widespread and that research comes
largely from single-site demonstrations. Studies focused on children’s early
care and education experiences from birth to age 5 include the Abecedarian
Project (Ramey & Ramey, 2006); the Milwaukee Project (Garber & Heber,
1981), the Brookline Early Education Project (BEEP; Bronson, Pierson, &
Tivnan, 1984; Pierson, Bronson, Dromey, Swartz, Tivnan, & Walker, 1983;
Pierson, Walker, & Tivnan, 1984), and the federal Comprehensive Child
Development Program (CCDP; St. Pierre et al., 1994). Most of the studies
employed a treatment versus control group experimental design. BEEP used a
within-treatment experimental design, randomly assigning participants to
varying levels of program services.

The Abecedarian Project (Ramey & Ramey, 2006) provided continuous
services for children in center-based settings from 4 months to the start of
kindergarten. Of the 111 children, half were randomly assigned to receive the
center-based program and half to a control group that received no program

BACKGROUND LITERATURE REVIEW

(both groups received health and social support services); children’s mothers
were primarily primiparous, African American, and single. Similarly, the
Milwaukee Project provided intensive, continuous, center-based and family
support services to a special population: an extremely small sample of 20
African American mothers with very low IQs (75 or below; Garber & Heber,
1981). The BEEP study randomly assigned parents and children to three
levels of intensity— (1) monthly home visits, meetings, and center-based child
care; (2) similar but less frequent services; or (3) information and support
at the center and by phone from birth to kindergarten. The CCDP provided
intensive family support services in 21 locations. CCDP emphasized case
management with family services and to a much lesser extent child
development services (St. Pierre et al., 1994).

Two of these evaluations reported very large effects on children’s
cognitive development (effect sizes of 1.0) at the time the program ended
and/or when children entered school (Garber & Heber, 1981; Ramey &
Ramey, 2006). The BEEP study observed social and emotional benefits among
treatment children (Pierson et al., 1983). The CCDP program did not
demonstrate cross-site positive outcomes, leading researchers to conclude
that family support programs not providing child development services were
not sufficient to affect child development (St. Pierre et al., 1994).

Birth to 5 programs have also been found to have positive impacts beyond
the intervention period. Most notably, the Abecedarian Project reported that
treatment children were less likely to be retained in grade or require special
education and were more likely to graduate from high school and attend
college (Ramey & Ramey, 2006). The treatment group had higher IQ, math,
and reading scores from age 8 to 21 (McLaughlin, Campbell, Pungello, &
Skinner, 2007; Ramey & Ramey, 2006). Milwaukee Project children at age 10
demonstrated an average IQ that was 20 points higher than that for the
control group (105 vs. 85; Garber & Heber, 1981). BEEP children were
observed in the spring of second grade, 3 years after the program ended, with
significant differences favoring the most intensive BEEP intervention
children found for reading and teacher-reported “learning skills” (Pierson
et al., 1984).

In summary, these evaluations provide evidence that early childhood
services, especially those that are educational, can influence child develop-
ment. However, these evaluations tell us little about how timing and duration
affect children’s development and parenting either directly or through
mediation effects. The infant and toddler programs may affect emotional as
well as cognitive development (especially if the program includes a center-
based component) and may influence parenting (especially if the program
includes a home-based or parent focus). Programs for 3- to 5-year olds (that
tend to be center-based) seem to have their strongest impacts on school-
related cognitive skills. Few evaluations of programs starting in the first year of

life and continuing until kindergarten have been conducted. One—the
Abecedarian Project with a strong center-based focus—had strong, lasting
child development impacts whereas another—CCDP with no center-based
focus—had few impacts, perhaps because its focus was on family support
rather than child development. We speculate that an optimal package of
services might include parent and child services in order to enhance child
social-emotional, language and cognitive outcomes and parenting in the
infant and toddler years, followed by formal care and education that is child
focused in the preschool years. However, except for some preliminary
findings pertaining to school readiness skills (e.g., preliteracy or math skills),
we know little about how broader domains (e.g., language, broad cognitive
development, or social-emotional development) might be differentially
affected by program timing, duration, or two-generation versus child-only
services, and we know little about how these effects might differ across
subgroups determined by family or program characteristics.

EFFECTS OF EARLY CHILDHOOD PROGRAMS ON CHILD OUTCOMES
WITHIN SUBGROUPS

It is somewhat challenging to determine whether programs are
differentially effective for subgroups, which is a question we would like to
address ultimately. In this monograph, three types of subgroups are
examined, based on program model of EHS service delivery, family race/
ethnicity, and family level of demographic risk.

Because infant and toddler early childhood programs are sometimes
home-based, sometimes center-based, and sometimes a combination of the
two, we cluster sites by the type of model employed. Effects may to be larger
and broader among programs offering a combination of home visiting and
center-based services (ACF, 2002a; Gomby, 2005), although direct tests of this
premise do not exist as programs were not randomly assigned to program
approach. For primarily home-based services, positive child outcomes have
been detected in areas related to health and safety (Johnson et al., 1993;
Kitzman et al., 1997) and, to a lesser extent children’s emotional functioning
(ACF, 2002a; Jacobson & Frye, 1991), whereas center-based programs tend
more frequently to report cognitive outcomes for children (e.g., Field,
Widmayer, Stringer, & Ignatoff, 1980; Ramey, Bryant, Sparling, & Wasik,
1985). Home-based programs often report positive effects on parents
(Howard & Brooks-Gunn, 2009).

We are interested in whether early childhood program opportunities and
effects vary for low-income children depending on race/ethnicity. For
example, many early childhood intervention studies have focused on at-risk
African American children (Olds et al., 2004; Ramey & Ramey, 2006; Reynolds

BACKGROUND LITERATURE REVIEW

& Temple, 2006; Schweinhart, 2006). With some exceptions (Gormley et al.,
2005), fewer studies have demonstrated effects for Hispanic children. The
IHDP (Brooks-Gunn et al., 1993) reported that children of African American
mothers were more influenced by the intervention than children of White
mothers at 2 years, possibly, as the authors note, because the former were less
educated and more poor.

Programs may differentially affect children and families with different
levels of risk. Previous evaluations have examined this premise. For example,
IHDP had the greatest impact on children’s cognitive development in families
where mothers had a high school education or less (Brooks-Gunn et al., 1992;
Liaw & Brooks-Gunn, 1993). Using a cumulative risk index rather than just
maternal education, effect sizes were largest for children whose families had
a moderate number of risks (Liaw & Brooks-Gunn, 1994). The NFP often
reports the most positive benefits for mothers with psychological and
emotional risk factors (Olds et al., 1994). Most intervention programs are
targeted at children at risk but there has been little standardization of
the variables used to define risk factors. In addition, intervention programs
serve different populations, both in terms of central tendency and
distribution. Moreover, who is at greatest risk in one cohort may differ
from who is at greatest risk in another cohort, even under the same definition.
Thus, it is difficult to compare whether the “highest risk” in one study is
comparable to “highest risk” in other studies. To distinguish EHS families
with different levels of risk, we counted up to five demographic risk factors
that families had when they enrolled: (1) being a single parent; (2) receiving
public assistance; (3) being neither employed nor in school or job training;
(4) being a teenage parent; and (5) lacking a high school diploma or GED. To
form groups of reasonable size, families were divided into three subgroups
based on the number of risk factors they had when they enrolled: (1) lower
risk families who had zero, one, or two risk factors; (2) moderate-risk families
who had three risk factors; and (3) highest risk families who had four or five
risk factors. Because the current study quantifies levels of risk, the findings
reported here should be helpful in beginning to clarify who benefits from
what combinations of services.

RESEARCH QUESTIONS AND HYPOTHESES

Despite over 40 years of research on effects of early childhood programs
on children’s development, surprisingly little is known about the timing of
intervention mechanisms by which programs affect development. We offered
theoretical perspectives earlier on how early and later experiences might
influence children’s development. These perspectives lead to the research
questions this monograph addresses in Chapters III–VI.

1. What were the impacts of EHS on children and parents when the
children were 2 and 3 years of age (age 3 being the end of the program) and 2
years after the end of the program when the children were age 5 (Chapter III)?

We expected that impacts would be seen across a range of outcomes when
the children were 2 and 3 years of age. Sustained impacts were expected at age
5, although effect sizes would be smaller than at ages 2 and 3, given that effects
in previous programs diminished several years after the intervention. Such
findings would be consistent with early experiences influencing development,
since the intervention experience, occurring in the first years of life, would
influence development later. We expect such effects, if found, to be most
pronounced for social and emotional outcomes. Consistent with the
hypotheses that pertain to intervention being particularly effective if offered
during specific periods of development, and that programs focused on
improving mother–child relationships, we expected that parental impacts
would be seen at age 2 on parenting measures that would mediate impacts of
social and emotional functioning in the children later on. We also expected
some impacts on parents to be sustained to age 5 as well (Howard & Brooks-
Gunn, 2009). Moreover, we expected that age 3 EHS impacts on children’s
language, cognitive, social, and emotional development would mediate age 5
impacts in similar domains. Furthermore, based on the expectation that EHS
would provide transition experiences for children (US DHHS, 1994), we
hypothesized that EHS would increase the probability that children would
participate in formal programs at ages 3 and 4. We further hypothesized that
EHS would increase the probability that children would enter HS.

2. What were the impacts of EHS on children and parents within
prespecified subgroups at ages 2, 3, and 5 (that is during, at the end of, and
following the intervention) (Chapter IV)?

It is important to know whether effects of EHS vary depending on family
and child characteristics. Differential treatment effects are examined for the
three racial/ethnic groups and for three groups of families defined by
number of risk factors. Some (but not all) evidence suggests that African
American children, and perhaps Hispanic children, show larger benefits of
early intervention than White children, although these links may be due, in
part, to the fact that even within low-income families, the former two groups
are less educated and poorer than the later group (Bassok, 2010; Brooks-
Gunn, et al., 1993).

3. What were the impacts of EHS across ages 2, 3, and 5 in the three
clusters of programs—those that offered home-based, center-based, or a
combination of the two? (Chapter V).

We expected that children and families in mixed-approach programs
would experience more positive age 3 outcomes than their counterparts, given
that they would have had the advantages of participating in programs with the
capacity to provide either or both home-based and center-based services to

BACKGROUND LITERATURE REVIEW

individual families in a flexible way designed to meet their specific goals and
needs. We expected more child impacts for center-based programs and more
parent-related impacts among participants in home-based programs.

4. What were the effects of out-of-home, formal preschool program
participation during the age 3–5 period and how did effects of children’s
experiences across the age 0–5 period accumulate (Chapter VI)?

This question asks whether some conditions post-EHS enhance or detract
from outcomes at age 5. Controlling for EHS use during the children’s years
from birth to age 3, we hypothesized that effects for preschool services
would be similar to what has been found in other studies in which school
achievement-related outcomes tend to be associated with formal care and
education experiences, if the care settings are of good quality (Gormley et al.,
2005; Magnuson & Waldfogel, 2005; NICHD ECCRN, 2005a). We also
expected that emotional outcomes would be related to program experience
in a negative way, consistent with the previous nonexperimental analyses
(Magnussun, Ruhm, & Waldfogel, 2007; NICHD ECCERN, 2005a).

We hypothesized that children who had both EHS (infant and toddler)
and preschool formal programs (ages 3–5) would fare the best at age 5,
consistent with the original theory of change for EHS that emphasized early
gains would be sustained and augmented by assisting EHS families find
preschool programs (US DHHS, 1994). As an overarching hypothesis we
hypothesized that experiences are incremental and augmented (NICHD
ECCRN, 2001), whereby later experiences during the preschool years would
build on early EHS impacts. At the same time, EHS impacts might act as a
buffer such that if preschool program attendance was associated with
aggressive behavior as others have found, EHS might offset this association
(NICHD ECCRN, 2003a; Magnusson et al., 2007). For cognitive, school
achievement-related outcomes, we predicted, as has been found in other
studies (Gormley et al., 2005; Magnusson et al., 2007; NICHD ECCRN, 2000),
that contemporaneous experiences from formal preschool education would
be linked to age 5 outcomes as would EHS intervention. As for school-
related outcomes, we predicted that EHS language impacts would be
strengthened among children who had attended formal programs. We also
hypothesized that parents in EHS would engage in more cognitive stimulation
and support for children’s development and that preschool attendance would
not be an influence, given that preschool education programs, in general,
spend less time working with parents than infant and toddler programs do.

NOTES

1. It has been the practice of Head Start to refer to the eligible population of “low-income”
families as those with annual incomes below the federal poverty level. In many research

contexts, however, “low income” refers to families whose incomes are below 200% of the
poverty threshold. However, to be consistent with usage within most Head Start and EHS
research, in this monograph we refer to the enrolled families as low income.

2. We have more than one reason for limiting our focus during the years 3–5 to formal early
care and education programs. First, drawing on an extensive literature pertaining to the
importance of center-based care for children during the prekindergarten years, the Advisory
Committee on Services to Families with Infants and Toddlers, the committee appointed by then
Secretary Donna Shalala to design what would become EHS, recommended that children
receive formal program services following EHS (U.S. Department of Health and Human
Services, 1994). Arguably, family support and home visiting services could be recommended for
children in families following EHS but this was not the specific recommendation of the
committee for all children and it is not the question addressed in this monograph. Second, few
children/families in the EHS sample, in either the program or control group, were enrolled in
exclusively home visiting services during the years 3–5, although families with children in HS
would have received at least two home visits a year, whereas formal care and education
experience for children was relatively common as will be shown.

3. Home visiting programs reach many children, most but not all of whom are served
during the years 0–3 and many but not all are considered low income or are otherwise at risk. As
of the early 2000s, as many as 400,000 children are served annually in home visiting programs, at
a cost of approximately $750 million to $1 billion and these numbers will expand under current
administration proposals (Gomby, 2005).

4. Children are less likely to enroll in HS or EHS, however, the higher their parents’ level of
education attainment, as would be expected given the income requirements and the
relationship between income and educational attainment (Iruka & Carver, 2006).

BACKGROUND LITERATURE REVIEW

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INFANT MENTAL HEALTH JOURNAL, Vol. 23(1 – 2), 231 – 249 (2002)
� 2002 Michigan Association for Infant Mental Health

A R T I C L E

EARLY HEAD START MAP: MANUALIZED

ASSESSMENT OF PROGRESS

SUSAN DICKSTEIN
RONALD SEIFER

MARIA EGUIA
REGINA KUERSTEN-HOGAN

KARIN DODGE MAGEE
Brown University School of Medicine, E. P. Bradley Hospital

ABSTRACT: We present the Early Head Start MAP (Manualized Assessment of Progress) system, a newly
developed program evaluation protocol for Early Head Start (EHS). Briefly, EHS is a prevention program
for low-income families with infants, toddlers, and pregnant women. The EHS MAP protocol was de-
signed to be incorporated into the fabric of the EHS program, utilized by all EHS staff members with
input from EHS families. As such, it serves to document ongoing progress of children and families while
enrolled in the program, as well as the fidelity of services provided. Preliminary empirical results are
presented to exemplify the nature of efficacy and fidelity data that can be obtained with this EHS MAP
system. Implications of conducting program evaluation are discussed as related to Early Head Startservice
delivery.

RESUMEN: En este estudio se presenta el sistema MAP (Evaluacio´n manualizada del progreso) de “Early
Head Start,” un protocolo para la evaluacio´n de programas recientemente desarrollado para “Early Head
Start.” En breve, EHS es un programa de prevencio´n para familias de bajos recursos econo´micos con
infantes, nin˜os que empiezan a dar pinitos, y mujeres embarazadas. El protocolo MAP fue disen˜ado para
ser incorporado dentro de la estructura del programa EHS, utilizado por todo el personal de EHS con
sugerencias de las familias de EHS. Como tal, el protocolo sirve para documentar el constante progreso
de los niños y familias que participan en el programa, ası´ como tambie´n la fidelidad de los servicios que
se prestan. Los preliminares resultados empı´ricos son presentados para ejemplificar la naturaleza de la
eficaz y fiel informacio´n que se puede obtener con este sistema MAP. Las implicaciones de llevar a cabo
una evaluacio´n del programa se discuten tal como se relacionan con el servicio de prestaciones de “Early
Head Start.”

RÉSUMÉ: Nous présentons le syste`me Early Head Start MAP. Le Early Head Start est un programme de
prévention et d’aide gouvernementale a` la petite enfance de´favorisée aux Etats-Unis d’Ame´rique. Le
MAP (Evaluation Manuelle de Programme, abre´gé MAP en anglais) est un protocole d’e´valuation de
programme tout nouvellement de´veloppépour le programme Early Head Start. Brie`vement, et plus spe´-
cifiquement, le EHS est un programme de pre´vention pour les familles a` bas revenus ayant des be´bés,

The authors wish to acknowledge collaboration with New Visions for Newport County, Inc., Early Head Start, and
Self Help, Early Head Start, in the development and implementation of this work. The authors are supported in part
by the National Institute of Mental Health. Direct correspondence to: Susan Dickstein, Bradley Hospital, Brown
University, 1011 Veterans Memorial Parkway, East Providence, RI 02806; phone: 401-751-8040; fax: 401-331-2768;
e-mail: Susan�Dickstein@brown.edu.

232 ● S. Dickstein et al.

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base of textdes petits enfants, et pour les femmes enceintes. Le protocole EHS MAP a e´téconçu pour être incorpore´

dans le tissu du programme EHS, utilise´ par tous les employe´s de EHS avec le concours des familles
participant au programme. En tant que tel, il sert a` documenter le progre`s en cours des enfants et des
familles pendant qu’elles sont inscrites au programme, ainsi que la fide´lité des services qui sont offerts.
Des résultats empiriques pre´liminaires sont pre´sentés afin d’exemplifier la nature de l’efficacite´ et la
fidélité des donne´es qui peuvent eˆtre obtenues avec ce syste`me EHS MAP. Les implications pour effectuer
une évaluation de programme sont discute´es comme e´tant liées au service qu’offre le EHS.

ZUSAMMENFASSUNG: Wir präsentieren das Early Head Start (EHS� Frühförderungsprogramm in den
USA) MAP (ein Manual zur Bestimmung der Fortschritte) – ein neuerdings entwickeltes Manual zur
Evaluation des Fru¨hförderungsprogramms EHS. In aller Ku¨rze gesagt ist EHS ein Vorsorgeprogramm
für einkommensschwache Familien mit Sa¨uglingen, Kleinkindern und fu¨r schwangere Frauen. Das EHS
MAP wurde so hergestellt, dass es in das Netzwerk des EHS passt und von allen MitarbeiterInnen und
Familien, die das EHS gestalten, verwendet werden kann. So dient es als eine Dokumentation der Ver-
laufsbeobachtung der Kinder und ihrer Familien, die am EHS teilnehmen und dokumentiert die Sicherheit
der Leistungserbringung. Vorla¨ufige empirische Daten werden pra¨sentiert, um die Art der Leistungsmes-
sung und deren Sicherheit zu zeigen, die mit dem EHS MAP System erhoben werden ko¨nnen. Die
Bedeutung einer Evaluation eines solchen Programms wird im Zusammenhang mit der Leistungserbrin-
gung des EHS diskutiert.

* * *

Children develop in context. Their outcomes reflect the risk and protective circumstances
of their early environments. Early Head Start (EHS), a federally funded prevention program,
was designed to promote the well-being of at-risk children by providing a healthy context in
which young children and their families can develop. The mission of EHS is to enhance chil-
dren’s physical, social, emotional, and cognitive development; to enable parents to promote
their child’s development, enhance parenting competence, and meet their own goals including
economic independence; to provide individualized child development, parent education, and
family-focused services; to use a plan developed by parents and staff that is supportive and
nurturing of families; to recognize child care needs of working families; to help them connect
with other community services; and to involve parents in policy and decision making at all
levels of the program. Further, this mission not only involves implementing the EHS program,
but also includes monitoring its effectiveness at both local and national levels.

Effective monitoring of EHS needs to incorporate all aspects of its impressive mission and
be flexible to meet the needs of the children, families, and staff associated with the program.
We designed the EHS Manualized Assessment of Progress (MAP) system as a program eval-

Early Head Start MAP ● 233

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base of textuation tool to be integrated within the fabric of the EHS program, utilized by all EHS staff

members with input from EHS families. As such, it serves to document on-going progress of
children and families while enrolled in the program, as well as the fidelity of services provided.

WHAT IS MONITORED?

The EHS MAP system can be used to monitor efficacy and fidelity of program implementation.
It can be used to assess and track individual child and family progress in five domains that are
related to the EHS mission. The five goal domains include: (1) Parent Self-Sufficiency; (2)
Child Developmental Readiness; (3) Parent Promotion of Child’s Development; (4) Health,
Nutrition, and Mental Health; and (5) Program–Community Integration. Three major factors
influenced the selection of goals within these five domains. First, they reflect the U.S. Depart-
ment of Health and Human Services, Administration on Children, Youth, and Families(ACYF),
Head Start Bureau’s “Head Start Program Performance Standards and Other Regulations,”
intended as a guide for EHS service implementation. Second, the goal domains reflect the
principal means by which the broad EHS mission, described at the outset, has been operation-
alized. Third, they highlight the empirical research findings on predicting child competence in
poverty samples. The specific goals that are chosen within each domain are detailed in Table
1. The selection of these specific goals was guided by empirical literature, and integrated the
collective years of experience and wisdom of the EHS staff with whom we collaborated in the
development of this system. It is important to note that additional specific goals of interest to
EHS programs that are not listed in the table can be easily incorporated into the current system.

Parent Self-Sufficiency

This goal domain focuses on the pragmatic aspects of family functioning. Each child’s partic-
ipation in EHS is embedded in his or her relationships with primary caregivers, which in turn,
are embedded in a family context, and further within neighborhood, economic, and cultural
circumstances (Sameroff, 1983; Chase-Lansdale et al., 1997). Recent research on poverty has
highlighted the complex interplay among family and environmental factors that are most related
to child outcomes (McLoyd, 1998), including the pragmatic aspects of family life. For EHS to
be most effective in addressing principles of development and adaptation, it is necessary for
the program to be maximally sensitive to this level of the child’s developmental context. EHS
MAP goals in this domain would be selected if the family indicates a particular need or desire
for improvement in areas such as income or finances, employment, obtaining basic resources,
credit history, child care, and/or education.

Child Developmental Readiness

The negative effects of poverty on child development are well documented and pervasive
(Halpern, 1993; Huston, McLoyd, Garcia Coll, 1994; McLoyd, 1998). This is even more con-
cerning given the recent trend for a gradual yet steady increase in poverty rates for children,
particularly preschoolers (McLoyd, 1998). Research has shown that poverty negatively affects
children’s cognitive development, academic achievement, and socio-emotional development
(McLoyd, 1988; McLoyd, Ceballo, & Mangelsdorf, 1996; Stipek & Ryan, 1997). The EHS
program is intended to promote optimal child outcomes, not only by facilitating pragmatic
family functioning (see above), but by providing services that directly improve or enhance the
child’s development. EHS MAP goals in this domain would be selected to facilitate the ac-
quisition, maintenance, and/or generalization of development in areas of language, fine motor,

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base of textTABLE 1. MAP Domains: Early Head Start Goals

(01). Parent Self-
Sufficiency

(02). Developmental
Readiness

(03). Parent Promo

tion

of Child Development

(04). Health, Nutrition,
and Mental Health

Wellness

01. Income
02. Employment
03. Basic resources:

Food
Housing
Clothing
Utilities
Health insurance
Transportation

04. Credit history
05. Child care
06. Registration

Birth certificates
Social security
Voting

07. Education
08 Other self-sufficiency

01. Developmental
milestones
Language
Gross motor
Fine motor
Adaptive
Cognitive
Specific milestone

02. Socialization
Classroom adjust-
ment
Behavior/emotions
Relationship with
Peers/caregivers

03. Transition plan
04. Developmental as-

sessment
05. Other readiness

01. Parenting skill
02. Family violence pre-

vention and interven-
tion

03. Family relationships
Adult relationships
Parent–child bond

04. Neighborhood safety
05. Home environment
06. Parent involvement
07. Other parent promo-

tion

01. Routine health care
Nutrition
Prenatal health
Family planning
Well-baby/child
checks
Health screens
Immunizations

02. Chronic/acute illness
03. Preventive mental

health care
04. Mental health treat-

ment
05. Behavioral health

care (e.g., addictions)
06. Social support
07. Other wellness

(05). Program–
Community Integration

01. Coordination among
service providers

02. Collaboration with
community services

03. Assessment/develop-
ment of community
resources

04. Other community

gross motor, cognitive and adaptive functioning. In addition, this domain includes tracking of
the child’s socialization capacities and behavioral adjustment.

Parent Promotion of Child Development

The EHS program emphasizes partnerships with families that is critically important for the
enhancement of child competence. The Early Head Start program is designed to serve families
in poverty, a context often associated with additional risks such as neighborhood violence,
teen- and single-parenthood, and nonoptimal parenting practices. Researchershavedocumented
that parents in impoverished contexts are more likely to use harsh, inconsistent, and coercive
parenting practices compared to parents with greater economic means (Lyons-Ruth, Zoll, Con-
nell, & Grunebaum, 1986; Sampson & Laud, 1994; Smith, Brooks-Gunn, & Klebanov, 1997).
Further, father absence is a critical variable for predicting child outcome in this context (Osof-
sky, Hann, & Peebles, 1993). Research findings are often contradictory regarding the degree
to which young fathers indicate desire to be involved in the parenting of their children (Chase-
Landsdale & Vinovskis, 1987; Furstenberg & Harris, 1993) and the degree to which nonresi-
dential fathers actually are involved in their children’s lives (Anderson, 1989; Sullivan, 1989).

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base of textHowever, the little research that is available suggests that involvement of fathers in the lives

of at-risk children is associated with better educational and behavioral child outcomes (Cook,
Church, Ajanaku, Shadish, Kim, & Cohen, 1996; Furstenberg & Harris, 1993).

Finally, it is crucial to recognize that family systems are not limited to the (so-called)
traditional nuclear family especially when working with at-risk populations. Impoverished and
minority populations are more likely to live in larger extended family networks or to utilize
extended family members to provide child care and basic necessities such as food, shelter, and
financial assistance (Garcia Coll, 1990; Halpern, 1993; Hunter, 1997; MacPhee, Fritz, & Miller-
Heyl, 1996; Pearson, Hunter, Cook, Ialongo, & Kellam, 1997; Pearson, Hunter, Ensminger, &
Kellam, 1990). Teenage parents, compared to older mothers, are also more likely to reside with
their own mothers (Burton, 1990; Osofsky et al., 1993; Wakschlag, Chase-Lansdale, & Brooks-
Gunn, 1996). Recent research has pointed to a complex interplay of the quality of the mother–
grandmother relationship, age of the mother, and mother and child characteristics in the effects
of mother–grandmother coresidence on child developmental outcomes. For example, having
a grandmother living in residence with teen and minority mothers is related to improvements
in parenting skills and child developmental outcomes (Apfel & Seitz, 1997; Kellam,Ensminger,
& Tuner, 1977; Osofsky et al., 1993). More specifically, grandmother co-residence is most
beneficial for children and teen mothers when the teen is younger (Chase-Lansdale, Brooks-
Gunn, & Zamsky, 1994; Wakschlag et al., 1996). Alternatively, older mothers who maintain
positive, supportive, and independent relationships with their own mothers demonstrate more
effective parenting skills when living apart from grandmothers (Wakschlag et al., 1996). The
grandparent–child relationship in and of itself may provide a protective function for young at-
risk children (Chase-Lansdale et al., 1994; Halpern, 1993) and certainly needs to be examined
when developing EHS goals for children and families.

Given the importance of parenting and family relationships for predicting childcompetence
in poverty samples, the EHS MAP system emphasizes this domain. EHS MAP goals related
to Parental Involvement in the Child’s Development include facilitating and/or enhancing par-
enting skills and family relationships (including parent–parent and parent–child bonds), as-
sessing the need for family violence prevention and/or intervention, and addressing issues
related to neighborhood safety and healthy home environments.

Health, Nutrition, and Mental Health Wellness

Children born in the context of poverty are more likely to have health problems including
prematurity; poor nutrition; increased rates of lead exposure; more frequent and longer hospital
stays; and prenatal exposure to alcohol, tobacco, and other drugs (Bradley, Whiteside, Mund-
from, Casey, Kelleher, & Pope, 1994; Halpern, 1993; McLoyd, 1998; Needleman, Schell,
Bellinger, Leviton, & Allred, 1990; Pollitt, 1994; Siegel, 1982). Further, mental health needs
of this population are rarely addressed. It is crucial that, given the needs of the vulnerable
children and families it serves, Early Head Start programs must attend to and fully integrate
mental health services to improve overall quality of relationships between EHS staff and fam-
ilies, as well as the larger childcare community (Mann, 1997).

In addition, the parents of these children are more likely to have health and mental health
difficulties that also affect child outcomes. For example, much research targeting the influence
of maternal depression on infant and child outcomes supports the notion that depressed mothers
display disruptions in parenting behavior, and that their children exhibit a variety of impair-
ments in social, psychological, and affective functioning (Dickstein et al., 1998; Lyons-Ruth
et al., 1990; Seifer & Dickstein, 2000; Weissman et al., 1987). EHS families are at high risk
for health and mental health problems given the burden of accumulated contextual risks. Teen-

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base of textage mothers have been found to have high rates of psychological distress, especially anxiety

and depression (Garrison, Schuluchter, Schoenback, & Kaplan, 1989; Kessler, Berglund, Fos-
ter, Saunders, Stang, & Walters, 1997; Osofsky & Eberhart-Wright, 1988; Osofsky et al., 1993).
Further, depression is more common in women without partners (as is frequently the case with
young mothers), and in the context of poverty (Bradley et al., 1994; Duncan, Brooks-Gunn, &
Klebanov, 1994; Planos, Zayas, Busch-Rossnagel, 1997; Sameroff, Seifer, & Bartko, 1997).

In sum, the health and mental health needs of families enrolled in EHS require attention
and documentation. Therefore, EHS MAP goals in this domain include routine health care,
health care for chronic or acute illness issues, mental health care (treatment)and/orconsultation,
behavioral health care, and/or social support.

Program– Community Integration

This goal domain focuses on two main issues related to establishing a coordinated system of
care for EHS families. Often times, and with all good intentions, families with multiple needs
are helped to access the variety of services they might require. However, they often are left
overwhelmed and befuddled by the numerous appointments, agencies, and care providers of-
fering assistance, yet operating independently of each other. Ultimately, this leads to families
withdrawing from obtaining the “help” they might need. One role of the EHS Family Advocate
is to serve as a coordinator of services. Thus, EHS MAP goals in this domain include the
coordination of services among multiple services, service providers, and/or agencies withwhich
the family is involved, linking families with community services, and facilitatingtheassessment
or development of community resources that might not be readily available.

Summary

The EHS MAP system can be used to track and monitor progress of individual children and
families during their enrollment in EHS. It guides the selection of goals that are relevant to the
EHS mission, and guides staff in their work with families. The EHS MAP system is embedded
in the day-to-day functioning of the EHS program. That is, all staff members working with
children and families enrolled in the program contribute to the documentation of progress. A
basic principle in designing the EHS MAP system was to employ activities that program staff
were already completing, and toorganize(developmentally and sequentially),systematize, and
track these activities in a data-based manner.

METHOD AND CASE VIGNETTE

As part of the routine EHS enrollment procedures, all members of the EHS team (including a
teacher, family advocate, mental health consultant, nurse, and nutritionist) met with Jimmy Z.
and his family to obtain basic information about child and family functioning (through inter-
view, testing, and observation of family interaction). During these meetings, EHS staff, in
partnership with the family, identified areas of strength as well as areas of nonoptimal func-
tioning, which are recorded using EHS MAP reviews.

Below, we briefly describe the main components of the MAP system, and use the case of
Jimmy Z. and his family to illustrate the dynamics of the system. These system components
include MAP reviews and goal plans. We then discuss the conversion of the MAP paperwork
into data used to provide feedback regarding program efficacy at the level of average child and
family progress.

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base of textMAP Reviews

The EHS MAP system is based on partnership efforts between EHS staff and families, as well
as coordinated efforts among EHS staff. To document results of these collaborations, three
reviews are completed. TheFamily Development Reviewis completed by the Family Advocate
(or Home Visitor) in conjunction with the family upon enrollment in the program. It documents
the family’s level on all EHS social service goals in domains of Parent Self Sufficiency, Parent
Promotion of Child Development, Health/Mental Health Wellness, and Program–Community
Integration. Although it is initially conducted as part of the family’s enrollment in the program,
it is updated quarterly during the time the family is enrolled in the program. Areas of nonoptimal
functioning and/or strong needs are identified as goals that comprise the Family Development
Plan (see below).

Also upon enrollment to the program, aDevelopmental Readiness Reviewis completed
by the primary care provider (teacher) to document the child’s level on all Child Developmental
Readiness goals. Ratings in all areas of child developmental readiness are guided by results of
a formal developmental assessment (conducted as a routine enrollment procedure). The De-
velopmental Readiness Review is updated and discussed with the family at least three times
per year. Goals for the Developmental Lesson Plan (see below) are chosen based on these
reviews, which reflect areas of nonoptimal development and/or strong needs.

The following vignette summarizes information obtained from EHS staff regarding Jimmy
Z. and his family shared at the initial Care Coordination meeting, based on EHS MAP review
information. Jimmy Z. was being considered for placement in a center-based full-day class-
room.

“Jimmy Z. is a nearly two-year-old boy who lives with his unmarried father and five-year-
old brother. Jimmy was placed in the care of his father (Mr. Z) two weeks prior to EHS
enrollment, after having resided in foster care since birth. Mr. Z reported that Jimmy was
removed from his mother’s custody at birth due to a positive toxicology screen, following
which she apparently made no attempt to regain custody of Jimmy, or reestablish a relationship
with Mr. Z. Jimmy’s brother had a similar early history, and had been in the sole custody and
care of his father for the past six months. Mr. Z had liberal visitation with Jimmy since birth,
and increased lengths of stay recently in preparation for the current placement. Mr. Z was
positive about his reunification with his son, and expressed realistic concerns about the chal-
lenges facing him as a single father of 2 young boys.

Mr. Z described his own history of drug and alcohol abuse, although indicated that he has
maintained sobriety for the past year. He also reported a sometimes-volatile relationshiphistory
with one adult partner. Mr. Z is employed fulltime, and has minimal social supports. He
identified a desire for general assistance with parenting.

Jimmy has a well-documented history of language delays, for which he was evaluated and
in treatment with the local Early Intervention agency. Mr. Z indicated that he was concerned
about Jimmy’s limited use of words. He otherwise described Jimmy as a robust child, with
minimal medical or nutrition difficulties.

Jimmy was observed to be a happy and sociable toddler. He engaged in exploratory be-
havior during most of the interview, examining just about every object in the room, and sharing
particularly fascinating discoveries with his father. In addition to abundant curiosity, Jimmy
was quite physically active, and was observed to nearly run into doors or walls on several
occasions. Mr. Z was appropriately vigilant to Jimmy’s activities, although demonstrated less
than effective limit setting abilities. The dyad engaged in warm and affectionate behavior.”

At the initial care coordination meeting, aCare Coordination Reviewwas completed by
the Care Coordination team leader to document family and child levels for all current (in

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base of textprogress) goals. The team reviews all child development and family goals, based on information

from the initial Developmental Readiness Review and initial Family Development Review, so
that the EHS team was aware of the initial goals to be addressed. Subsequent to this initial
meeting, care coordination meetings are held to review each child’s and family’s progress at
least on a monthly basis, with input provided by all EHS staff involved with the family. The
team meeting serves to coordinate efforts among EHS staff in their work with a particular child
and family. During this time, staff members participate in a discussion and planning session
regarding all in-progress goals as well as other issues that require attention.

In the case of Jimmy Z., the team reviewed information about the child’s developmental
status, as well as family functioning. The team (with input from Mr. Z during the enrollment
process) identified the following initial goals. The EHS teacher selected a “Language” goal for
Jimmy, and the Family Advocate selected a “Parenting Skill” goal. The selection of these goals
was consistent with the parent’s input. It should be noted, however, that other goals may have
been equally appropriate for this family (such as Parental Social Support, Adult Relationships,
and/or Coordination of Community resources), and which may flexibly be selected at any time
while the child is enrolled in the program.

Developmental Lesson Plan (DLP)

Using the MAP system to monitor the child’s developmental progress, the child’s teacher rates
selected Child Developmental Readiness goals using the Developmental Lesson Plan. This
includes a series of goal sheets, one for each of the Child Developmental Readiness goals.
Goals are chosen for an individual child based on information obtained from developmental
screening assessments, classroom observations, and family reports of the child’s strengths and
needs. When relevant, the DLP incorporates goals originated in other service agencies (such
as Early Intervention). Note that we use the language of the center-based program component
(e.g., teacher developed plans), but there are equivalent functions performed by home visitors
in the home-based portion of the program.

The DLP is reviewed on a weekly basis by the teacher to plan and track the child’s activities
and progress in the particular goal area—it is a continual “work in progress” as the child grows
and develops. The steps to achieve each goal (termed “accomplishments”) are listed, by chron-
ological age, to facilitate the planning and monitoring process. An example of a DLP goal
sheet (targetingLanguagedevelopment) and the accompanying Accomplishment Manual page
(for Languagedevelopment) are presented in Tables 2 and 3, respectively.

Family Development Plan (FDP)

Using the MAP system to monitor family progress, the Family Advocate together with the
family selects at least one goal to be rated using the Family Development Plan goal sheet. This
document is family-focused, addresses family needs and desired goals, and like the child-
focused DLP is a continual work in progress. Following an initial family needs assessment
target goals are chosen in at least one of the four family-based domains consistent with the
EHS mission (described in the Introduction). The FDP is reviewed on a regular basis to plan
and track the family’s progress on selected goals. Akin to the DLP, the accomplishments that
may be chosen en route to achieving goal progress are provided in list form to facilitate the
planning and monitoring process. An example of an FDP goal sheet (targetingParenting Skill)
and the accompanying Accomplishment Manual page are presented in Tables 4 and 5, respec-
tively.

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base of textTABLE 2. Example of Developmental Lesson Plan (DLP) Goal Sheet for Language Development

DEVELOPMENTAL LESSON PLAN (Week of )

Child Name: Staff: Reviewed with Family□

0201 (Development—Language) Date Initiated:
Initial Goal Level:
Desired Goal Level:

(Circle Current Goal Level)
0. On Hold
1. Nonoptimal development; evidence of impairment
2. Nonoptimal development; no impairment
3. Development generally on track; some inconsistencies
4. Development on track; solidly within normal limits
5. Maintenance/consolidation of gains
6. Generalization/enhancement of gains

Accomplishments End of Week Review
Date

Completed

1. # Incomplete—No Progress
Incomplete—Progress
Completed

2. # Incomplete—No Progress
Incomplete—Progress
Completed

3. # Incomplete—No Progress
Incomplete—Progress
Completed

4. # Incomplete—No Progress
Incomplete—Progress
Completed

5. # Incomplete—No Progress
Incomplete—Progress
Completed

6. # Incomplete—No Progress
Incomplete—Progress
Completed

Activities:

Codifying Progress in Goal Domains

Each child and family enrolled in EHS works with a multidisciplinary team on at least one
child and one family goal. For each goal, objective and measurableGoal Levels(from absent
to sufficient) are established, rated when the goal is initially identified, and updated regularly.
SpecificAccomplishmentsare determined to help promote progress toward each goal in smaller
chunks. Accomplishments are reviewed and rated regularly (as “incomplete- no progress,”

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base of textTABLE 3. Example of Accomplishment Manual for Language Development

Language Age Range

01. Child smiles 0–3 months
02. Child coos
03. Child orients to voice

04. Child vocalizes pleasure, displeasure, eagerness, satisfaction 4–9 months
05. Child babbles (vowels, consonants, multisyllables)
06. Child produces at least three different sounds
07. Child listens selectively to familiar words (bath, name for bottle, going

out)
08. Child spontaneously uses gestures

09. Child plays gesture/language games (pat a cake, so big) 10–15 months
10. Child uses dada and mama specifically
11. Child understands and responds to “no”
12. Child uses one word
13. Child imitates sounds
14. Child follows one step command with adult’s gesture (“Come to

mommy”)
15. Child imitates words
16. Child speaks two to six words
17. Child uses jargon (babbles with inflection)
18. Child uses exclamatory expressions
19. Child uses pointing and reaching to communicate needs
20. Child can identify familiar objects/people
21. Child labels/says animal sounds

22. Child speaks 7 to 20 words 16–24 months
23. Child uses words to make needs/wishes known
24. Child uses two-word combinations
25. Child can name up to 30 pictures
26. Child speaks 50 words
27. Child labels body parts
28. Child uses words to describe actions

29. Child uses two- to three-words sentences 25–36 months
30. Child uses pronouns
31. Child understands prepositions
32. Child uses descriptives
33. Child uses 50–100 words
34. Child can name 31–100 pictures

“incomplete-some progress,” or “completed”). This is a unique aspect of the MAP system in
that specific goals are broken down into manageable steps that are easily tailored to individual
needs and strengths, that are developmentally appropriate, and simultaneously keep both the
big picture and the little pictures in sharp focus. A Manual of Accomplishments is provided
(and updated at regular intervals) to effectively guide staff to develop systematic, coherent
plans with families to facilitate progress on goals.

Computer Data Entry

On a weekly basis, MAP goal levels and accomplishment ratings are entered into the computer
for data analysis. The data are organized such that each record represents a specific goal,

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base of textTABLE 4. Example of Family Developmental Plan (FDP) Goal Sheet for Parenting Skill

FAMILY DEVELOPMENT PLAN—CONTACT NOTE

Name: Date: Reviewed with family□

0301 (Parenting Skill) Date Initiated:
Initial Goal Level:
Desired Goal Level:

(Circle Current Goal Level)
0. On Hold
1. Nonoptimal evidence of impairment
2. Nonoptimal no evidence of impairment
3. Adequate but inconsistent or undesirable
4. Adequate and consistent or desired
5. Better than adequate; maintain/enhance gains

Accomplishments Visit Review
Date

Completed
1. # Incomplete—No Progress
Incomplete—Progress
Completed
2. # Incomplete—No Progress
Incomplete—Progress
Completed
3. # Incomplete—No Progress
Incomplete—Progress
Completed
4. # Incomplete—No Progress
Incomplete—Progress
Completed
5. # Incomplete—No Progress
Incomplete—Progress
Completed
6. # Incomplete—No Progress
Incomplete—Progress
Completed

Notes:

recording overall goal level, specific accomplishments, and whether progress was made in the
last time period. Also, the type of staff member implementing this part of the individualized
plan is recorded. Goals are coded in such a way that specific domains and developmental level
are easily determined. The result is a database that is time-based relative to each goal identified
in the child/family’s individual plan, and data can be flexibly organized depending on the type
of report required.

242 ● S. Dickstein et al.

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base of textTABLE 5. Example of Accomplishment Manual for Parenting Skill

Goal 03. Parent promotion of child development

Goal 0301. Parenting skill

General parenting issues
01. Obtain information regarding normative child development
02. Expand repertoire of behavior management techniques
03. Establish consistency in parenting between adult caretakers
04. Coordinate behavior plans between home and EHS
05. Enhance ability/amount of time to play with child
06. Use proper child safety restraints/learn about child-proofing home
07. Balance work/family issues
08. Attend parenting groups/workshops/training/socialization
09. Attend individual parenting meetings
10. Obtain information about specific developmental milestone(s)
11. Obtain information about specific child difficulty (e.g., night terrors)
12. Coordinate across agencies regarding parenting issues
13. Access/attend community resource related to child development (like library, playground, etc.)

Language
51. Repeat infant’s vocalizations
52. Talk to infant/toddler during diaper change, feeding, dressing, and other caretaking tasks
53. Read books to the child at least once per day
54. Label objects and people child points to
55. Sing songs to the child
56. Encourage child to use language to express needs
57. Obtain information about developmentally appropriate language skills

Gross motor
101. Provide child with push and pull toys to strengthen muscles
102. Encourage child to move his/her body by gently turning child side to side or stomach to back to strengthen

muscles
103. Hold child’s hands and pull child to stand to practice leg muscles
104. Provide child with safe environment to practice crawling/walking
105. Hold child’s hands and let child walk
106. Take child to outdoor/indoor playground to provide opportunity for gross motor activity
107. Lay child on stomach during waking hours to strengthen back muscles
108. Practice walking up and down the stairs
109. Encourage child to roll and catch ball on the floor
110. Encourage child to throw ball
111. Encourage child to hop
112. Encourage child to run
113. Play dancing games with the child in which the child has to copy the leader’s moves

RESULTS

To use the MAP system to assess efficacy within the program, program functions need to be
specified from which progress and adherence can be determined. An example is provided below
with respect to child and family outcomes in a local EHS program based on a four-month
period of time. Data is based on enrollment of 108 children and their families; 40 children
were in a home-based program and 68 were in a center-based program. (More specifically, we
will report on information obtained from families whose children were enrolled in the program
for at least seven weeks. This is a relatively arbitrary cut-off, but one that likely yields data
that reflect progress made by children and families who were fully engaged with the program).
Using this system, we report on a total of 69 center-based and 23 home-based families.

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base of textTABLE 6. Average Progress Made in EHS Center-Based Program on Child-Focused Goals (n � 69)

Goal Domain
Initial Goal

Levela
Current

Goal Level

Average
Change in
Goal Level

Number of Completed
Accomplishments per

Goal
Number of
Children

Developmental readi-
ness

2.9 4.1 1.2 5.7 69

Health, nutrition, mental
health wellness

2.4 4.2 1.8 8.1 46

aGoal level: 1–2� Nonoptimal; 3� adequate but inconsistent; 4–6� on track.

Although the main purpose of this article is to describe the program evaluation system,
we provide preliminary results to exemplify the type of data that can be obtained. We list only
a small subset of the questions that can be asked of the MAP system data to illustrate its
functionality. These include:

1. What is the average initial goal level of all center-based children in the EHS program
in the domain of developmental readiness?

2. What is average amount of progress in the domain of developmental readiness during
the quarter?

3. What is the average number of accomplishments that are completed related to goal
progress?

4. What are the results of questions 1–3 (above) with respect to the children and families
enrolled in the home-based program?

Center-Based Child Outcomes

Table 6 indicates that all (100%) children had individual developmental readiness goals se-
lected, worked on, and monitored during the quarter. This is consistent with Program Require-
ments. Most (67%) of children had health, nutrition, and/or mental health wellness goals se-
lected during the quarter. This reflects the relatively high number of children for whom medical,
nutritional, and/or mental health issues necessitated attention by EHS. On average, substantial
progress was made on goals selected in both domains for the quarter. In both domains, children
were functioning at nonoptimal levels at the time the specific goals were selected. By the end
of the quarter, children were rated as solidly on track. Goal level progress was associated with
completion of accomplishments. On average, children completed six to eight accomplishments
in each goal domain.

Center-Based Family Outcomes

Table 7 indicates that Parent Self-Sufficiency goals were selected by 57% of families. Parent
Promotion of Child Development goals were selected by 77% of families. On average, in both
goal domains, some progress was made during the quarter. In the Parent Self-Sufficiency
domain, families were initially rated as functioning at nonoptimal levels. By the end of the
quarter they progressed to adequate but inconsistent levels of functioning. Families made sim-
ilar progress in the Parent Promotion of Child Development domain, although level of func-

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base of textTABLE 7. Average Progress Made in EHS Center-Based Program on Family-Focused Goals (n � 69)

Goal Domain
Initial Goal
Levela
Current
Goal Level
Average
Change in
Goal Level
Number of Completed
Accomplishments per
Goal
Number of
Children

Parent self-sufficiency 2.6 3.1 0.5 2.1 39
Parent promotion of child
development

3.2 3.6 0.4 2.6 53

Average across parent-
focused goal domains

2.9 3.4 0.5 2.4

aGoal levels: 1–2� Nonoptimal; 3� adequate but inconsistent; 4–6� on track.

TABLE 8. Average Progress Made in EHS Home-Based Program on Child-Focused Goals (n � 18)

Goal Domain
Initial Goal
Levela
Current
Goal Level
Average
Change in
Goal Level
Number of Completed
Accomplishments per
Goal
Number of
Children
Developmental readi-
ness

2.7 3.6 0.9 2.4 18b

Health, nutrition, mental
health wellness

3.0 3.9 0.9 4.2 13

aGoal levels: 1–2� Nonoptimal; 3� adequate but inconsistent; 4–6� on track.
b Note that 5 of the 23 participants enrolled were pregnant women; 18 were children.

tioning did not change by the end of the quarter. This may reflect that goals were initiated
when families demonstrated adequate (although inconsistent) levels of functioning.

Home-Based Child Outcomes

Table 8 indicates that all (100%) children had individual developmental readiness goals se-
lected, worked on, and monitored during the quarter. This is consistent with Program Require-
ments. Most (57%) of children had health, nutrition, and/or mental health wellness goals se-
lected during the quarter. This reflects the relatively high number of children for whom medical,
nutritional, and/or mental health issues necessitated attention by EHS. On average, substantial
progress was made on goals selected in both domains for the quarter. In the Developmental
Readiness domain, children were functioning at nonoptimal levels at the time the specific goals
were selected. By the end of the quarter, children were rated as adequate. In the Health domain,
children were functioning at adequate levels at the time the specific goals were selected. By
the end of the quarter, children were rated as nearly on-track with respect to these issues.

Home-Based Family Outcomes

Table 9 indicates that Parent Self-Sufficiency goals were selected by 61% of families. Parent
Promotion of Child Development goals were selected by 48% of families. In the Parent Self-
Sufficiency domain, families were initially rated as functioning at nonoptimal levels. Although
some progress was made, on average, families continued to function at this level at the end of

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base of textTABLE 9. Average Progress Made in EHS Home-Based Program on Family-Focused Goals (n � 23)

Goal Domain
Initial Goal
Levela
Current
Goal Level
Average
Change in
Goal Level
Number of Completed
Accomplishments per
Goal
Number of
Children

Parent self-sufficiency 1.6 2.0 0.4 1.6 14
Parent promotion of child
development

2.2 3.3 1.1 2.3 11

Average across parent-
focused goal domains

1.9 2.7 0.8 2.0

aGoal levels: 1–2� Nonoptimal Functioning; 3� adequate but inconsistent; 4–6� on track.
b Note that 5 of the 23 participants enrolled were pregnant women; 18 were children.

the quarter. Families made solid progress in the Parent Promotion of Child Development do-
main, and level of functioning improved from nonoptimal to adequate by the end of the quarter.

Summary

It seems likely that in this EHS program, home-based families, on average, are the most vul-
nerable or fragile. Even with substantial progress made on selected goals, functioning continues
to be in the nonoptimal range. Also, working on accomplishments made a difference for goal
levels—on average, the more accomplishments completed, the greater the change in goal level.
On average, goal levels changed more dramatically for child-focused goals than for parent-
focused goals, possibly because (especially center-based) children are in more frequent contact
with EHS professionals compared with their home-based counterparts.

DISCUSSION

The Early Head Start Manualized Assessment of Progress was designed to be embedded within
the fabric of daily operations of the program. This reflects our belief that evaluation is most
efficient and accurate when the evaluation data are created as part of everyday activities per-
formed by program staff. Furthermore, the organization imposed by structured evaluation ac-
tivities is more likely to have positive effects on quality of intervention when the activities are
closely tied to program functions. The system we have described here documents continuous
improvement and growth in the context of ongoing social, developmental, and/or familial
challenges. Further, it provides opportunity for families and staff to receive regular feedback
about progress.

Understanding Outcomes

The data we presented suggested that progress was made in child development and family goal
domains. It is important to clarify that the MAP system is not a developmental assessment, per
se. Rather, it is a system that facilitates the selection and attention to particular child and family
areas identified either as a strong need. Once a goal has been adequately achieved, new goals
are selected. Further, the same goal may be selected on different occasions, as circumstances
change for the family. For example, a parent may identify to her Family Advocate that she
requires a car without which she is unable to work. Together, they agree to select a “transpor-
tation” goal in the Parent Self-Sufficiency” domain; the initial goal level would be rated

246 ● S. Dickstein et al.

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base of textin the nonoptimal range. After working together for 3 months to save money and locate an

appropriate car, the family advocate and parent agree that the goal has been adequatelyachieved
(the goal rating would then be changed to reflect this improvement, and the goal is no longer
targeted). However, six months later, the car breaks down, again leaving the family with no
means of transportation (at which point the goal is reselected, and the goal level is againinitiated
in the nonoptimal range).

Thus, the MAP system is used to characterize and monitor the progress made on salient
child and family goals. Snapshot assessments (e.g., quarterly reports) of the data are taken to
give the program feedback about the nature of their work with the families they serve. We
have presented data aggregated for the program as a whole (to describe program efficacy),
although data can be analyzed at the level of individuals, as well.

Implications of Program Evaluation for Early Head Start
Service Delivery

Implementation of the EHS-MAP involved intensive training of all EHS staff in assessment of
normativechild development. Such basic training is consistent with the tenets of thedevel-
opmental psychopathologyagenda that has been well articulated by Ciccetti, Rutter, Emde,
Sameroff, and others (e.g., Sameroff & Emde, 1989). Not only is it important that EHS staff
have good understanding of the interplay of normative and maladaptive processes, but also
that they focus on thecontext in which behavior occurs. That is, while the individual psycho-
logical existence of infants and toddlers is one important framework, it is crucial to place
developmental understanding in context of the child’s family/caregiving environment. EHS
can be a unique resource for helping young families maintain and capitalize on their strengths
in the service of making strides toward optimal growth and development.

First and foremost, good program evaluation can help guide programs to most effectively
provide services to optimize chances for positive development for children and families. But,
evaluation can serve other important functions as well. One of these functions is to improve
the quality of services delivered in the program. At this time we have anecdotal information
to suggest that implementation of the EHS-MAP system has served to enhance the quality of
service by fostering cooperation among EHS team members; facilitated staff-family partner-
ships; challenged staff to flexibly address child and family needs; and required staff to regularly
monitor and evaluate service provision and utilization. Thus, if the specific programming used
is better matched with individual families’ needsand the programming itself is of higher
quality, then children’s development may be doubly enhanced.

A related issue is the function of staff supervision within a complex program such as EHS.
The implementation of the EHS-MAP system underscored the importance of this supervision,
both at the level of individual staff members interacting with professionals with different areas
of specialization, as well as in the domain of collaborative peer supervision. As staff members
better understood the boundaries of their expertise, the most effective ways of delivering spe-
cific interventions, and methods for maximizing collaboration between professionals with di-
verse expertise, they became more effective change agents for the EHS children and families.
In addition, the structure of the evaluation process also served to maintain the focus of EHS
providers on proactive strength-based case management, as opposed to “putting out the fires”
identified in a crisis intervention mode. In sum, there are many potential ways to use this
system in supervision. First, the process of goal selection is an opportune time for individual
supervision to focus on child and family developmental agendas and trajectories. Second, data
can be analyzed on various levels (program, classroom, individual staff member, individual

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base of textchild or family, etc.); this flexibility allows for exploration of patterns of progress, both for

EHS clients and staff. Third, program level feedback can be used to inform issues such as
future program planning, allocation of resources, and qualifications of staff that best match
client needs.

FUTURE DIRECTIONS

The EHS MAP system shows initial promise, but future work should be directed toward further
establishing its utility in evaluating EHS program goals. Furthermore, it would be useful to
determine whether the evaluation structure also provides feedback to programs resulting in
improved quality. We emphasize that it is important not only to evaluate program effectiveness
in EHS, but to do so in the best possible manner. The purpose of this article was to introduce
the system, and to describe our initial impressions of its utility within the EHS program. We
believe that the next step clearly needs to be an empirically based validation study to fully
understand its scope and limitations.

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198

Applying a Response-to-Intervention Model
for Early Literacy Development in
Low-Income Children

Maribeth Gettinger
University of Wisconsin–Madison
Karen Stoiber
University of Wisconsin–Milwauke

This article describes the design and implementation of a program that incorporates a response-to-intervention (RTI) framework
for promoting the development of early literacy and language skills among low-income minority children. The early liter-
acy program, called the Exemplary Model of Early Reading Growth and Excellence, or EMERGE, combines classroom
practices that are grounded in empirical research, a multitiered intervention hierarchy, high-quality professional develop-
ment, and continuous progress monitoring to help children in Head Start classrooms acquire early literacy competencies to
prepare them for later success in school. Preliminary program evaluation data are presented, and challenges associated with
applying an RTI model in early childhood education are addressed.

Keywords: early literacy; response-to-intervention; progress monitoring; multitiered instruction; Head Start

Learning to read and write begins early in children’sdevelopment, long before they enter kindergarten.
Moreover, literacy skill development in early childhood
provides the foundation for children’s long-term acade-
mic success. Over the past two decades, researchers have
identified key emergent literacy skills that develop pro-
gressively in children during their preschool years and
are highly predictive of later success in learning to read
(Burns, Griffin, & Snow, 1999; Casey & Howe, 2002;
Neuman & Dickinson, 2001; Whitehurst & Lonigan,
1998, 2001). These skills include phonological aware-
ness (e.g., hearing and manipulating smaller sounds in
words), letter knowledge (e.g., identifying and naming
letters), print awareness (e.g., noticing print and follow-
ing words on a page), and oral language (e.g., describing
events and telling stories).

Many young children face significant challenges in
learning to read because they lack essential early literac

skills when they begin school. In fact, children who are
poor readers at the end of elementary school are most
often those who fail to develop early literacy skills dur-
ing preschool and kindergarten (Torgesen, 1998).
Deficits in early reading skills at the beginning of kinder-
garten tend to remain, or even increase, through elemen-
tary school, creating a continuously widening gap
between children who have good literacy skills and those

who do not (Badian, 2000; Foorman, Francis, Fletcher,
Schatschneider, & Mehta, 1999; Juel, 1988; Scarborough,
2001; Snow, Burns, & Griffin, 1998; Stanovich, 2000).
Unfortunately, children who enter kindergarten with lim-
ited literacy and language skills rarely catch up and are
at high risk of being referred for special education ser-
vices (Whitehurst & Lonigan, 1998, 2001). A child who
completes second grade without being able to read, for
example, has only a 25% chance of reading at grade level
by the end of elementary school (Snow et al., 1998).
Furthermore, the majority of children with reading diffi-
culties in Grade 4 will continue to have reading problems
at the end of high school, and they have a higher proba-
bility of dropping out of school (Scarborough, 2001).

Topics in Early Childhood
Special Education

Volume 27 Number 4
Winter 2007 198-213

10.1177/0271121407311238
http://tecse.sagepub.com

hosted at http://online.sagepub.com

Authors’ Note: This study was supported, in part, by the U.S.
Department of Education, Office of Elementary and Secondary
Education, Early Reading First Program Grant S359A040145. Any
opinions, findings, and conclusions or recommendations expressed in
this publication are ours and do not necessarily reflect the views of
the U.S. Department of Education or those of the University of
Wisconsin. We thank the teachers, children, and staff of the Social
Development Commission–Head Start in Milwaukee who partici-
pated in this study. Please address correspondence to Maribeth
Gettinger, Educational Psychology, University of Wisconsin, 1025
W. Johnson Street, Madison, WI 53706; e-mail: mgetting@wisc.edu.

Additional research has identified risk factors that make
certain groups of children particularly vulnerable to diffi-
culties in acquiring early literacy skills (Bryant, Burchinal,
Lau, & Sparling, 1994; Snow et al., 1998). Weaknesses in
skills and subsequent reading failure are most common
among low-income, non-White children and among
children with limited proficiency in English (Hart &
Risley, 1995; Snow et al., 1998). For example, on the 1998
National Assessment of Educational Progress (National
Center for Education Statistics, 1999), 68% of fourth
graders who qualified for free or reduced lunch scored
below the basic level of achievement in reading, compared
to only 25% of students who did not qualify for reduced
lunch. The development of children’s language and literacy
is heavily influenced by home literacy practices. Compared
to children from middle-income families, children from
economically disadvantaged families experience signifi-
cant difficulties learning to read and write because they
enter school with lower knowledge of letters and less
familiarity with words. Children from low-income families
and with limited English proficiency are often reared in
homes that fail to provide sufficient early literacy experi-
ences and materials to promote print-related skills; their
families typically do not support the acquisition of literacy
skills to the same degree that parents of higher socioeco-
nomic status do (Campbell, Goldstein, Schaefer, & Ramey,
1991; Lonigan, Burgess, Anthony, & Barker, 1998). For
example, middle-income children begin school having had
as many as 6,000 books read to them, whereas children
from low-income families may start school without ever
having been read to at home (Moustafa, 1997).

Collectively, these findings underscore the importance
of developing and implementing models to promote
early literacy development among young, at-risk
children to ensure they enter kindergarten with the requi-
site skills and knowledge to become successful readers.
High-quality early intervention programs can reduce the
number of children who enter school with weak literacy
skills. According to the National Research Council,
implementing evidence-based emergent literacy strate-
gies in preschool can prevent reading problems in ele-
mentary school and ultimately reduce the need for
special education services (Snow et al., 1998).

The recent shift toward implementing a response-to-
intervention (RTI) model with low-achieving elementary
and secondary students is consistent with the current
emphasis on prevention and early intervention for
preschool children (Batsche et al., 2005; Fuchs & Fuchs,
2006). Inherent to an RTI approach is the practice of pro-
viding high-quality instruction and supplemental individ-
ualized support, based on children’s needs, through a
multitiered model. RTI hinges on the use of systematic

screening and progress monitoring to enable teachers to
provide well-targeted instruction and individualized sup-
port when delays are evident. Specifically, children who
are not making adequate progress toward developing early
literacy skills are identified on the basis of progress-
monitoring data and provided with scaffolded instruction
to meet their needs (Coleman, Buysse, & Neitzel, 2006).

The focus of RTI on prevention, research-based inter-
ventions, and data-based decision making is clearly
aligned with the goals of early intervention. Nonetheless,
RTI models have not been widely implemented or docu-
mented in early education contexts (VanDerHeyden &
Snyder, 2006). Some multitiered intervention models have
been described in the early intervention literature. Sandall
and Schwartz (2002), for example, developed a model of
teaching young children with special needs in preschools.
Their model incorporates a tiered intervention hierarchy
that includes making curriculum modifications, embed-
ding a focus on individual children’s objectives in typical
classroom activities, and providing individualized instruc-
tion aimed at achieving individualized education program
goals. More recently, a multitiered model for intervening
with young children at risk for learning disabilities, titled
Response and Recognition, has been developed at the
University of North Carolina’s Frank Graham Porter Child
Development Institute (Coleman et al., 2006). This model
is designed to help teachers recognize early indicators of
learning delays and, in turn, respond with appropriate
instruction and assistance. With these exceptions, how-
ever, most of the literature documenting the application of
RTI to early intervention focuses on challenging behaviors
in young children, not necessarily on early literacy skills
(e.g., Barnett et al., 2006).

The purpose of this article is to describe the design,
implementation, and preliminary evaluation of an early
intervention model for promoting the development of emer-
gent literacy skills among low-income, minority children in
the context of community-based Head Start settings. The
program described in this article demonstrates the applica-
tion of an RTI framework and multitiered intervention
model for enhancing early literacy competence and, in turn,
preventing reading failure and the need for special educa-
tion among high-risk young children. After a description of
the early childhood context for the program, we explain the
four interrelated RTI components and demonstrate their
implementation in Head Start classrooms.

Overview of Program

The early literacy program described in this article,
called the Exemplary Model of Early Reading Growth

Gettinger, Stoiber / Response-to-Intervention Model 199

200 Topics in Early Childhood Special Education

and Excellence, or EMERGE, is a partnership between
the Social Development Commission (SDC) Head Start
of Milwaukee, the Head Start–Day Care Partner Program
of Milwaukee, and the University of Wisconsin in
Milwaukee and Madison. The EMERGE program is an
Early Reading First project funded through the U.S.
Department of Education (2005–2008). Through a com-
bination of (a) classroom practices grounded in empiri-
cal research, (b) a multitiered intervention hierarchy, and
(c) high-quality professional development, EMERGE is
designed to help children from low-income families
acquire early literacy skills to prepare them for later suc-
cess in school.

Participating Sites, Teachers, and Children

The EMERGE program includes 15 classrooms housed
in five center-based, early childhood programs that serve
low-income families residing in racially segregated and cul-
turally diverse neighborhoods in Milwaukee, Wisconsin.
The participating classrooms provide full-day, year-
round programming for children across 2 consecutive
years prior to kindergarten entry. Classrooms are staffed
by one lead teacher (who holds at least an associate’s
degree in early child education) and a classroom aide;
each classroom enrolls about 18 to 20 children.
Approximately 90% of the children in EMERGE are
from families that meet income guidelines for the federal
poverty level. The majority of children are African
American (90%–95%), with 6% to 10% of Hispanic ori-
gin and less than 2% White/other.

Conceptual Framework for EMERGE

Within the past decade, several comprehensive reports
have synthesized the converging evidence about the
development of early literacy skills, including Teaching
Our Youngest (Early Childhood–Head Start Task Force,
2002), Preventing Reading Difficulties in Young Children
(Snow et al., 1998), Teaching Children to Read (National
Reading Panel, 2000), and Put Reading First: The
Research Building Blocks for Teaching Children to Read
(Armbruster, Lehr, & Osborn, 2003). Collectively, these
sources have provided evidence that (a) learning to read
is based on the foundation skills of phonological aware-
ness, oral language, alphabet knowledge, and print aware-
ness; (b) children who have acquired these skills profit
more from formal reading instruction than do children
without them; and (c) reading success requires coherent,
intentional instruction in these skills before entering
kindergarten. Building on this evidence base, the
EMERGE program is predicated on the assumption that
children require continuous exposure to and structured

interaction with print; frequent oral and written language
interactions with adults; and systematic, explicit instruc-
tion to develop skills. In addition, EMERGE is based on
the knowledge that literacy environments play a key role
in developing children’s language and early reading
skills. Finally, EMERGE is grounded in the belief that
early childhood teachers require sustained, high-quality
professional development to be successful in promoting
children’s literacy development.

Program Goals and RTI Components

Based on these conceptual understandings of early lit-
eracy development, the EMERGE program targets four
interrelated goals. The first is to develop and implement
a multitiered instructional model that (a) maximizes the
use of research-based practices to support children’s
development of four early literacy skills; (b) increases
the amount of time children are engaged in interactive
shared book reading; and (c) incorporates the use of a
thematic, integrated, research-supported curriculum. The
second goal is to implement screening and progress-
monitoring procedures to identify children who require
more intensive intervention than what is provided
through the instructional and environmental enhance-
ments in the regular classroom. The third goal is to cre-
ate high-quality, literacy-rich learning environments that
support the development of young children’s early liter-
acy and language skills and promote positive learning
behaviors. The final goal of EMERGE is to provide
intensive and continuous professional development and
ongoing literacy coaching that is grounded in scientifi-
cally based knowledge of early literacy development.

Consistent with these program goals, EMERGE incor-
porates the following key components of an RTI approach:
(a) scientifically based early literacy curriculum, instruc-
tion, and activities provided at increasing levels of intensity
across a three-tiered intervention hierarchy; (b) screening,
monthly progress monitoring, and outcome assessment to
guide instructional decision making and identify children
who require a more intensive focus on early literacy skills;
(c) high-quality, literacy-rich classroom environments; and
(d) ongoing professional development combined with liter-
acy coaching and collaborative planning.

Another critical component of the EMERGE program
is family involvement. Because of the important role
families play in promoting young children’s literacy
development, the family involvement component of
EMERGE may be conceptualized as one aspect of
evidence-based practice within the multitiered model.
For purposes of this discussion, however, we have lim-
ited our description of intervention tiers to practices that
are implemented specifically in the context of Head Start

Gettinger, Stoiber / Response-to-Intervention Model 201

Figure 1
Exemplary Model of Early Reading Growth

and Excellence (EMERGE) Multitiered
Intervention Hierarchy

Tier 2:
Daily

Small-Group
Instruction

Tier 3:
Individual
Tutoring

Tier 1:
SECP Curriculum

SOAP Activities
Shared Book Reading

Literacy-Rich Environment

classrooms. Nonetheless, it is important to note that as
part of the EMERGE program, a family literacy center
operates 1 day every week in participating early child-
hood sites. This center is staffed by literacy specialists
who offer suggestions to families about home-based
activities and allow parents and children to sign out
developmentally appropriate books to read together at
home. In addition, included in the EMERGE literacy
resources are take-home books and nursery rhymes that
are read multiple times with children in classrooms and
distributed to families on a weekly basis. Finally,
families receive a monthly newsletter that describes the
curriculum theme, target letters, and theme-related activ-
ities to complete with children at home.

In the following sections, we describe the develop-
ment and implementation of the four EMERGE compo-
nents. In addition, we present preliminary program
evaluation data and discuss conclusions regarding the
application of RTI to early childhood education.

Three-Tiered Intervention Hierarchy

High-quality instruction is essential for early literacy
skill development in young children. The notion of qual-
ity in early literacy instruction is multidimensional and
includes the classroom environment, teaching behaviors,
and curriculum materials. The use of a three-tiered inter-
vention hierarchy ensures that all children have access to
high-quality early literacy practices. The tiers in the
EMERGE hierarchy represent increasing levels of inten-
sity and individualization of early literacy instruction,
which has been found to be effective through empirical
research. As shown in Figure 1, Tier 1 includes a
research-supported curriculum, a literacy-rich environ-
ment, and instructional activities to support children’s
development of phonological awareness, oral language,
alphabet knowledge, and print awareness. In Tier 1, the
focus is on optimizing the quality of the overall environ-
ment and classroom practices to promote early literacy
development among all children. Teachers participate in
professional development, weekly coaching sessions,
and collaborative planning to provide high-quality, sci-
entifically based instruction and to create literacy-rich
classrooms. Tier 2 (see Figure 1) includes daily, teacher-
directed, small-group instruction that provides greater
exposure to language and print, additional practice with
literacy skills, and/or activity adaptations for groups of 4
to 6 children based on their individual needs. Similar to
the support provided to teachers for Tier 1 instruction, all
teachers and aides receive training and coaching to plan
and implement Tier 2 instruction. Finally, Tier 3 (see

Figure 1) includes intensive, individualized tutoring
whereby children receive explicit and highly focused
training in early literacy skills from specialized early lit-
eracy tutors. Tier 3 instruction is provided for children
identified to be at highest risk for developing reading
difficulties (i.e., approximately 20% of children scoring at
the lowest levels on early literacy screening measures).
Support for Tier 3 tutors, who are preservice education
students at the University of Wisconsin, includes participa-
tion in 3-hour training sessions and regular group meetings.

Whereas each tier in the EMERGE hierarchy differs in
the intensity and individualization of early literacy instruc-
tion provided, two key features are constant across all tiers.
First, the activities and strategies provided within each tier
are designed to achieve the same core literacy goals and
incorporate scientifically based practices for early literacy
development. There is a common emphasis across all tiers
on strengthening fundamental skills that have been shown
to predict optimal reading development in elementary
school. In EMERGE, we use the acronym SOAP to help
teachers, classroom aides, and tutors remember these
skills. The letters in SOAP stand for sound awareness
(rhyming, alliteration, segmenting, blending), oral lan-
guage (vocabulary development, expressive language, lis-
tening comprehension), alphabet knowledge (letter
recognition), and print awareness. In effect, each

Note: SECP = Scholastic Early Childhood Program; SOAP = sound
awareness, oral language, alphabet knowledge, and print awareness.

202 Topics in Early Childhood Special Education

EMERGE tier represents an increasingly stronger focus
on, and greater assistance with, acquiring SOAP skills.
Using alphabet knowledge as an example, all children
receive instruction on target letters every week as part of
the regular classroom activities (Tier 1). By providing
children with multiple opportunities to respond during Tier
1 instruction, teachers are able to observe students’ levels
of alphabet knowledge. In addition, monthly progress
monitoring enables teachers to determine which children
require extra practice on letter identification. Based on
progress-monitoring data, as well as on teachers’ observa-
tions during instruction, children are selected to receive
additional support and instruction during teacher-directed,
small-group activities (Tier 2). Finally, data from screening
and midyear outcome assessment are used to identify the
lowest 20% of students; these students are provided with
intensive and individualized practice focusing on alphabet
knowledge (Tier 3).

A second common feature across all intervention tiers
is the adherence to a consistent curricular sequence (e.g.,
standard progression through content themes, focus on
the same target letters, etc.) and reliance on manualized
strategies (described later) to guide the provision of
instruction and/or tutoring. Furthermore, monthly profes-
sional development sessions, combined with weekly on-
site coaching and collaborative planning with the
EMERGE literacy coach, enable teachers to implement
scientifically based practices with high levels of integrity.

Both features of the EMERGE tiered intervention
model represent notable departures from the typical
application of RTI with older children. Within an RTI
model for older students, Tier 2 and Tier 3 interventions
are often conceptualized as different from Tier 1 univer-
sal interventions, rather than as a stronger dosage of the
same content. Another distinction is the higher degree of
flexibility and frequency in movement between tiers in the
EMERGE model based on multiple indicators of children’s
responsiveness to Tier 1 instruction. Development of
young children’s emergent literacy skills is characteristi-
cally sporadic and variable over time. Thus, determining
the need for Tier 2 scaffolded instruction may rely on
teachers’ ongoing observations of children’s progress and
performance during everyday learning situations, in addi-
tion to monthly progress-monitoring data. Despite these
important distinctions, the conceptualization and design of
intervention tiers in EMERGE are highly consistent with
an RTI approach, as described in the following.

Tier 1 Instruction

The first step in EMERGE’s multitiered approach is
establishing exemplary, scientifically based literacy

practices within each classroom by focusing on environ-
mental quality (which is a separate program component,
as discussed later), a comprehensive curriculum, and
research-based early literacy strategies. Tier 1 instruction
is built around three core elements. The first is the use of
a research-supported curriculum, specifically the
Scholastic Early Childhood Program (SECP; Block,
Canizares, Church, & Lobo, 2003). SECP is a compre-
hensive curriculum that integrates a primary emphasis on
language and literacy with other learning domains,
including math, science, and social studies. The curricu-
lum is structured around a set of 3-week, thematic units.
Based on input from EMERGE teachers regarding their
students’ learning needs, each SECP unit was extended
to cover 4 to 5 weeks to provide expanded coverage of
vocabulary and literacy concepts and additional review
of target letters. SECP is organized around daily routines
based on current knowledge of best practices in early
childhood education (Neuman, Copple, & Bredekamp,
2000). The curriculum provides explicit guidelines for
structuring each day to include whole-group circle time,
student-directed learning centers, story time, and
teacher-guided transitions. The high degree of structure
in SECP was deemed important for SDC Head Start
teachers, many of whom have limited prior professional
training in scientifically based early literacy practices.

The second element of Tier 1 is the provision of
teacher-directed SOAP activities through large- and
small-group instructional formats. To standardize this ele-
ment across classrooms and to promote intervention
integrity, a scripted manual of evidence-based strategies
that support the development of sound awareness, oral
language, alphabet knowledge, and print awareness was
developed by the program directors (the authors). This
manual, titled SOAP Strategies: Building Blocks of Early
Literacy, is provided to all teachers. For each SOAP skill,
the manual (a) describes and defines the skill, (b) explains
its importance for literacy development, (c) lists 3 to 5
developmentally appropriate goals (e.g., “Children will
recognize or ‘read’ familiar environmental print, espe-
cially common signs and classroom labels”), and (d) pro-
vides 8 to 10 pages of research-supported instructional
strategies for strengthening each skill. To ensure imple-
mentation of SOAP strategies, teachers’ weekly lesson
plans include structured SOAP activities for at least 10 to
15 minutes each day. The EMERGE literacy coach con-
ducts classroom observations on a biweekly basis using
the week’s lesson plan as an integrity checklist. During
the 2005–2006 school year, EMERGE teachers imple-
mented, on average, 90% of lesson plan components,
with 100% implementation of daily SOAP activities.

Gettinger, Stoiber / Response-to-Intervention Model 203

The third element of Tier 1 instruction is adult–child
shared book reading (SBR; Whitehurst et al., 1999).
Adult–child interactions during book reading have a sig-
nificant positive impact on children’s emergent literacy
(Justice & Kaderavek, 2002). Specifically, children learn
more from books when they are actively involved in read-
ing them. In EMERGE, we use the term shared book
reading, or SBR, to refer to this component of Tier 1
instruction. Two types of evidence-based practices are
incorporated into daily SBR: (a) dialogic reading
(Whitehurst et al., 1999), which includes asking open-
ended questions, following children’s answers with addi-
tional questions, repeating and expanding what children
say, and following children’s leads and interests and
(b) print referencing (Ezell & Justice, 2000), which
includes talking about print (e.g., “Where is the letter A
on this page?”) and pointing to print during reading.
Similar to SOAP strategies, to standardize the SBR ele-
ment across classrooms, teachers receive a manual, titled
Shared Book Reading to Promote Early Literacy and
Language Skills, which includes (a) activities to guide
teacher–child interactions before reading (e.g., children
make predictions), during reading (e.g., children respond
to open-ended questions), and following reading (e.g.,
children retell the story) and (b) activity cards that provide
scripted interactions and questions to accompany individ-
ual books supplied to classrooms. (See Appendix A for an
example of an SBR activity card.) In addition to theme-
related books that accompany the SECP curriculum,
teachers receive 5 to 7 thematic books with at least one
book from each of five categories (rhyming/alliteration,
repetition/pattern, knowledge/nonfiction, math/science
content, social/multicultural). To ensure implementation
of SBR strategies, teachers’ weekly lesson plans include
at least two book-reading sessions (20–25 minutes), one
in the morning and another in the afternoon. Classroom
observations of book-reading periods during 2005–2006
indicated that teachers appropriately implemented SBR,
on average, 90% of the time (i.e., used selected books and
implemented print referencing, dialogic reading, and
other strategies from the activity cards).

Tier 2 Instruction

Tier 2 small-group instruction is provided for children
who need extra assistance to make adequate progress in
developing early literacy skills. Research shows that a
small-group format may be more effective in helping
children acquire SOAP skills compared to a large-group
format for teaching the same skills (Elbaum, Vaughn,
Hughes, & Moody, 1999). Tier 2 instruction is provided
directly by teachers in classrooms to small groups of
children. Tier 2 includes planned, teacher-directed activities
that are designed to provide a stronger focus on SOAP

skills for small groups of 4 to 6 children and to adapt
SOAP strategies to children’s needs, such as focusing on
fewer alphabet letters at one time, providing additional
practice with simple rhyming patterns, or adding more
kinesthetic–tactile activities.

To guide the implementation of Tier 2 instruction, a
manual of evidence-based strategies was developed
through collaboration with SDC and EMERGE staff.
Specifically, a Tier 2 Task Force, including the program
directors, the EMERGE literacy coach, five SDC Head
Start teachers, and SDC site supervisors, held multiple
meetings to review the SECP curriculum and design sup-
plemental small-group activities aimed at strengthening
the focus on SOAP skills. The resulting manual, titled
Small-Group Activity Curriculum Supplement, is pro-
vided to each teacher and classroom aide to assist in
planning and implementing small-group activities.

The Tier 2 manual is divided into two sections.
Section 1 is titled General SOAP Activities. These activ-
ities are designed to be used across all curriculum themes
and focus on the development of SOAP skills. Three sub-
sections (Alphabet Knowledge Activities, Sound
Awareness Activities, and Oral Language and Print
Awareness Activities) include detailed descriptions of 25
to 30 small-group activities. Section 2 of the Tier 2 man-
ual is titled Theme-Related Activities. This section
includes developmentally appropriate activities designed
to supplement the thematic content of the core SECP
curriculum. Each subsection includes 10 to 13 small-
group activities that combine a relevant thematic focus
with an emphasis on SOAP skills as well as suggestions
for integrating math or science concepts into the activity.
(See Appendix B for an example of a theme-related
activity description.) Similar to all EMERGE compo-
nents, Tier 2 small-group activities from the manual are
included in weekly lesson plans, and implementation is
observed biweekly by the literacy coach.

Tier 3 Instruction

Tier 3 instruction is provided by tutors who are under-
graduate and graduate students in early childhood educa-
tion, elementary education, or school psychology at the
University of Wisconsin– Milwaukee. All tutors (N = 15)
participate in a 3-hour training session conducted by the
first author, with follow-up sessions at 3-month intervals.
Each tutor receives a tutoring kit (alphabet cards, alphabet
puzzle, writing tools, and other resources) and a scripted
tutoring manual. Tutors also have access to a develop-
mental range of books from each of the five categories
(listed earlier) and additional tutoring resources.

Tier 3 instruction is provided individually to children,
two to three times weekly. Each 20-minute tutoring

session includes two components: (a) SBR (children and
tutors read developmentally appropriate books together)
and (b) letters and sounds (tutors provide explicit instruc-
tion in letter naming, letter writing, alliteration, and
rhyming). Each tutor adheres to the same schedule of tar-
get letters and themes as in EMERGE classrooms such
that Tier 3 instruction serves to extend and reinforce the
instructional focus of Tier 1 and Tier 2. Similar to Tiers 1
and 2, Tier 3 individual tutoring is guided by a manual of
research-based activities that include SBR (dialogic read-
ing and print-referencing strategies) and SOAP strategies.
To maintain communication and collaboration between
teachers and tutors, tutors complete individual logs,
which are kept in the classrooms, detailing the activities
and children’s progress during tutoring sessions.

Screening, Progress Monitoring, and
Outcome Assessment

Implicit in the tiered intervention model of EMERGE
is a link to child data as the basis for instructional deci-
sion making. The assessment component of EMERGE is
designed to incorporate the use of screening and
progress-monitoring procedures that have good predic-
tive utility for identifying preschool children at risk for
reading failure and to ensure that instruction is scaffolded
across tiers to meet all children’s needs. Moreover, the
assessment component is multidimensional (focusing on
several dimensions of early literacy including vocabu-
lary, phonological awareness, letter knowledge, and oral
language) and combines both norm-referenced and
informal assessments of children’s skills.

Screening and Outcome Assessment

Screening data (collected in September) are used to
(a) establish a baseline level of functioning for all
children and (b) identify the lowest performing 20% of
children to receive Tier 3 individual tutoring during the
first half of the school year. We decided to provide 20%
of EMERGE children with Tier 3 instruction instead of
the 5% to 10% of children who are estimated to require
Tier 3 interventions in most RTI models (see Batsche
et al., 2005). This decision was based on the overall high
level of risk among children at baseline. For example,
approximately 60% of the sample scored below the nor-
mative average on the Peabody Picture Vocabulary
Test–III (PPVT-III; Dunn & Dunn, 1997). Subsequent
midyear assessment data (January) are used to (a) evalu-
ate the effectiveness of EMERGE for all children, (b)
determine environmental or instructional modifications
needed in individual classrooms, and (c) identify the

lowest 20% of children to receive Tier 3 tutoring during
the second half of the year. Finally, the end-of-year
assessment (May) provides an evaluation of the benefits
of EMERGE for all children.

The screening and outcome assessment battery
includes three measures that are administered individu-
ally to children by trained testers three times each year
(in September, January, and May). The measures include
(a) the Phonological Awareness and Literacy Screening–
PreKindergarten (PALS-PreK; Invernizzi, Sullivan,
Meier, & Swank, 2004), (b) the PPVT-III, and (c) an
informal oral-story-retelling measure that we developed.

The PALS-PreK (Invernizzi et al., 2004) is designed
to measure preschoolers’ developing knowledge of liter-
acy skills that are predictive of future reading success
(median correlation with kindergarten reading is .70).
Trained EMERGE testers administer three subtests from
the PALS-PreK as part of the comprehensive screening
and assessment battery. The first subtest, Name Writing,
is a strong indicator of early literacy development given
its well-established link to letter recognition and print
awareness (Welsch, Sullivan, & Justice, 2003). The sec-
ond subtest, Alphabet Knowledge, is also included as a
monthly progress-monitoring measure (described later).
For this task, children name uppercase alphabet letters
presented in random order, identify lowercase letters (if
16 or more uppercase letters are named), and produce the
sounds associated with letters (if 9 or more lowercase
letters are named). The third subtest, Print and Word
Awareness, uses a book-reading activity to assess
children’s awareness of print concepts such as direction-
ality, function of book parts (e.g., title), and the differ-
ence between pictures and words.

The informal oral-story-retelling task was developed
specifically for EMERGE as a measure of oral expressive
(speaking) vocabulary and of memory and comprehension
of short stories. Oral-story retelling is a good predictor of
a child’s reading success. Numerous studies support the
use of story retelling for a variety of diverse learners,
including young children, low-ability readers, and
children with limited English proficiency (Searfoss,
Readence, & Malette, 2001). The oral-retelling task devel-
oped for EMERGE involves reading aloud a short story
(90–95 words) that has three accompanying pictures (one
picture for approximately every 30 words). After hearing
the story and seeing the pictures, children are asked to
retell everything they remember about the story (while
looking at the pictures). Scoring of children’s retelling is
based on the number of main ideas they accurately retell.

Finally, the PPVT-III (Dunn & Dunn, 1997) is admin-
istered as a measure of children’s receptive (listening)
comprehension and vocabulary acquisition. This test is the

204 Topics in Early Childhood Special Education

most widely used, norm-referenced measure of vocabulary
for individuals who exhibit a range of diverse abilities.
According to the Center for the Improvement of Early
Reading Achievement, children’s early literacy skills build
on a strong foundation of vocabulary and language devel-
opment (Armbruster et al., 2003). Thus, vocabulary is
included among the skills that are necessary for learning
to read and serves as a good indicator of children’s early
literacy development (Scarborough, 2001).

Progress Monitoring

In EMERGE, children’s responsiveness to Tier 1
instruction is monitored by classroom teachers on a
monthly basis. In addition, aggregated classroom progress-
monitoring data are used to determine the extent to which
Tier 1 instruction is effective in promoting progress in lit-
eracy skill development among all children and/or whether
teachers need assistance in integrating a stronger focus on
SOAP skills. As such, progress-monitoring tools that accu-
rately reflect a child’s ability to benefit from instruction are
a key feature of EMERGE.

In recent years, significant progress has been made
toward developing individual growth and development
indicators (IGDIs), which are useful for screening and
monitoring skills that reflect progress in early literacy
and language development among preschool children
(Early Childhood Research Institute on Measuring
Growth and Development, 1998; Missel, McConnell, &
Cadigan, 2006). IGDIs are comparable to the progress-
monitoring procedures used with older students in that
they are quick and easy to administer by classroom
teachers and they are sensitive to growth over short peri-
ods of time (i.e., 1 month). EMERGE teachers receive
training and on-site coaching to administer and use the
information obtained from progress-monitoring proce-
dures (see the Professional Development section).

Three IGDIs (described in the following) are adminis-
tered individually to children by classroom teachers or
aides at 1-month intervals, during the third week of every
month. Progress monitoring occurs during times of the
day that are routinely scheduled for learning centers.
During the morning or afternoon center time, children
rotate individually through the progress-monitoring cen-
ter. The administration of the IGDIs requires 6 to 8 min-
utes per child. Thus, EMERGE teachers report they are
able to complete all progress monitoring for children
within a 4-day period.

The three IGDIs that comprise the progress-monitoring
measures are Picture Naming, Rhyming, and Alliteration
(Early Childhood Research Institute on Measuring
Growth and Development, 1998). For Picture Naming,

children are shown pictures of objects on individual
cards and given 1 minute to name as many pictures as
possible. For Rhyming, children have 2 minutes to view
individual cards each with a stimulus picture (e.g., car)
and three response-choice pictures (e.g., house, star,
dog). For each card, children point to the response-
choice picture that rhymes with the stimulus picture. The
format for Alliteration is similar to the rhyming task,
except that children point to the response-choice picture
that starts with the same sound as the stimulus picture. In
addition to these three IGDIs, progress monitoring
includes the Alphabet Knowledge subtest of the
PALS-PreK.

Monthly progress-monitoring data are used to identify
the lowest performing 50% of children for Tier 2 small-
group instruction. Teachers receive a graphic summary
of both individual child data and aggregated classroom
data (average scores) prepared by EMERGE staff.
Teachers use this information, first, to make decisions
about homogeneous Tier 2 small-group formation.
Children (4–6) in the lowest 25% of the class comprise
one small group, and children (4–6) in the next highest
25% comprise another small group. The decision to pro-
vide 50% of EMERGE children with Tier 2 instruction
(vs. 10%–25% who are estimated to require Tier 2 inter-
ventions in most RTI models) was based on several fac-
tors. First, using this decision rule allows teachers to
maximize the support provided to high-risk preschoolers
through small-group instruction. Second, the decision rule
is applied to performance across all progress-monitoring
measures. Thus, if a child is in the lowest 25% on
Rhyming and the lowest 35% on Alphabet Knowledge,
he or she will receive Tier 2 instruction. Finally, daily
attendance typically varies among Head Start children.
Using this decision rule ensures that small groups
include at least 3 children every day.

High-Quality Literacy-Rich Environments

This third program component focuses on the design
and structure of classroom environments to promote the
development of children’s language and literacy.
Children’s literacy skills and behaviors are strongly
influenced by features of the environment, including the
arrangement of learning centers, availability of materials
for reading and writing, and displays of print around the
room. Effective literacy environments are characterized
by three features (Dickinson & Sprague, 2001; Makin,
2003). First, materials are available and space is orga-
nized to facilitate frequent engagement in meaningful lit-
eracy activities. For example, literacy-rich classrooms

Gettinger, Stoiber / Response-to-Intervention Model 205

surround children with accessible, high-quality books;
diverse writing materials; and models of language and
print (e.g., labels, signs, posters, displays of children’s
writing, etc.). Second, within literacy-rich environments,
teachers function as active facilitators of children’s lan-
guage and literacy. They establish positive, nurturing
relationships with children; encourage children to
express themselves; model reading and writing behav-
iors; talk about environmental print in the classroom and
community; embed new vocabulary into conversations;
and promote oral language in social or play contexts
(Massey, 2004). Third, high-quality environments provide
frequent and sustained opportunities to engage in
literacy and language activities, especially through literacy-
enriched play. Through literacy play, there is a deliberate
integration of thematic literacy props into play settings,
combined with adult mediation and scaffolding of
children’s interactions with props (Justice & Pullen, 2003;
Neuman & Roskos, 1993). In addition, diverse literacy
materials (books, writing tools, alphabet display, etc.) are
available in activity centers around the room (e.g., math,
science, drama, construction, etc.) to promote the integra-
tion of literacy with other developmental domains.

In the EMERGE program, these features of high-quality
literacy environments are evaluated through systematic
classroom observations conducted by trained observers
using the Early Language and Literacy Classroom
Observation (ELLCO) system (Smith & Dickinson, 2002).
ELLCO includes an evaluation of each environmental fea-
ture and provides a summary of the overall quality of a
classroom in relation to early literacy skill development.
Available research indicates acceptable construct validity
and interrater reliability for the ELLCO, as well as utility
for measuring environmental changes across time (Smith
& Dickinson, 2002). ELLCO yields a total maximum score
of 70 distributed across three parts: (a) the Literacy
Environment Checklist (LEC), (b) one 40-minute class-
room observation and follow-up teacher interview, and (c)
the Literacy Activities Rating Scale (LARS). The LEC
focuses on classroom organization and literacy materials. It
consists of 24 items that are scored using either a yes–no
format (e.g., “Is an area set aside just for book reading?”)
or a rating indicating the number of literacy materials avail-
able (e.g., “How many varieties of teacher dictation are on
display in the classroom?”). The classroom observation
occurs continuously over a 40-minute period of time dur-
ing which there is a teacher-directed focus on literacy
activities. Observers note and rate the frequency and qual-
ity of language- and literacy-related teacher interactions
and behaviors. Finally, the LARS includes items related to
book-reading and writing activities in the classroom
throughout the day.

A summary of beginning-of-year observations (con-
ducted in September) with specific guidelines and crite-
ria for strengthening classroom environments is provided
to teachers during the professional development and
coaching sessions in October. In 2005–2006, the average
total ELLCO score for EMERGE teachers in September
was 47.18 (SD = 7.47). End-of-year observations (May)
yielded an average total ELLCO score of 63.44 (SD =
4.11), reflecting significant improvement in the quality
of environments, t(14) = 7.59, p < .001, and reduction in the overall variability of quality across classrooms.

Professional Development

The final component of EMERGE is teacher profes-
sional development. Teachers’ knowledge and use of
scientifically based classroom practices are central to
the implementation of an RTI model. The EMERGE
professional development component is designed to
improve teachers’ understanding of language and liter-
acy and their application of evidence-based practices.
This is achieved through two types of professional
development activities. First, EMERGE teachers partic-
ipate in monthly 3-hour professional development
training sessions (presented by the program directors)
to acquire the skills and resources necessary for (a)
implementing Tier 1 instructional elements (SECP cur-
riculum, SOAP strategies, and SBR), (b) conducting
monthly progress monitoring, (c) using information
about children’s early literacy performance to alter Tier
1 instruction and/or to plan Tier 2 small-group instruc-
tion for identified children, and (d) designing high-
quality literacy environments. The professional
development sessions are designed to combine didactic
training (guided by the content and strategies of the
SECP and other EMERGE manuals described previ-
ously) with collaborative planning among teachers and
whole-group sharing of successful classroom practices.
Opportunities are provided during each professional
development session for classroom teams (teacher and
aide) to collaborate with the program directors and/or
other teams to address challenges in implementing Tier
1 and Tier 2 instruction. In addition, teacher teams are
encouraged to showcase activities found to be particu-
larly effective in their classrooms.

The second type of professional development
involves on-site early literacy coaching and mentoring
and collaborative planning with the literacy coach for 2
hours every week (per classroom). The EMERGE liter-
acy coach has an advanced degree in early childhood edu-
cation and certification as an early literacy coach. The
objectives of literacy coaching are to model strategies;

206 Topics in Early Childhood Special Education

Gettinger, Stoiber / Response-to-Intervention Model 207

work one-on-one with teachers and children; monitor
implementation integrity through observations; and pro-
vide scaffolded, individualized support for teachers.

Preliminary Evaluation of EMERGE

An initial evaluation of the EMERGE program was
completed in August 2006 following 1 year of imple-
mentation in 15 classrooms. Preliminary comparisons of
children’s performances on key outcome measures in
EMERGE classrooms versus control classrooms suggest
that the multitiered, scientifically based instruction of
EMERGE is associated with higher performance across
multiple indicators of early literacy and language
development.

To conduct the program evaluation, 10 SDC Head
Start classrooms were randomly selected to serve as a
control group. Similar to EMERGE classrooms, 90% of
the children in control classrooms were from families
that meet income guidelines for the federal poverty level.
In addition, 92% of children were African American, 7%
were of Hispanic origin, and 1% were White/Other. All
teachers in EMERGE and control classrooms were
women (with the exception of one male classroom aide
in an EMERGE classroom). Table 1 summarizes addi-
tional characteristics of EMERGE and control classroom
teachers.

The beginning-of-year (September) and end-of-year
(May) performance of children in EMERGE and control
classrooms is summarized in Table 2 on eight outcome mea-
sures: IGDI Rhyming, Alliteration, and Picture Naming;
story-retelling task; PPVT-III; and uppercase letter
knowledge, print and word awareness, and name writing
from the PALS-PreK. It is important to note that these
performance data are aggregated across all ages, includ-
ing 5-year-old children who entered kindergarten in Fall
2006 and 3- and 4-year-old children with 1 or 2 more
years of preschool experience (including EMERGE)
before starting kindergarten.

As shown in Table 2, each measure exhibited moder-
ate correlations with the other outcome measures. As
expected, the correlation between PPVT-III and Picture
Naming (both measures of oral vocabulary) was strong
(r = .51), as was the correlation between Rhyming and
Alliteration (r = .59), which are both measures of phono-
logical, or sound, awareness. Multiple analyses of covari-
ance were conducted to examine differences between
children in EMERGE and those in control classrooms on
each outcome measure at the end of the year (May),
covarying for beginning-of-year (September) performance.
On each measure, EMERGE children outperformed

children in the control classrooms. Effect sizes ranged
from .13 to .45.

Conclusion

EMERGE is an early literacy program designed to pro-
vide multitiered, scientifically based instruction to low-
income children to ensure they begin kindergarten with
the fundamental skills necessary for learning to read.
Conceptualized within an RTI framework, EMERGE
relies on monthly progress-monitoring data and ongoing
observations by trained teachers to provide whole-group
instruction, small-group support, and individualized
tutoring for children to promote their early literacy and
language development. Through EMERGE, early identi-
fication of children who do not respond to Tier 1 instruc-
tion, combined with the provision of literacy-rich
environments and evidence-based instruction across all
intervention tiers, contributed to higher performance on
multiple early literacy and language indicators compared
to children in comparable Head Start classrooms.

Table 1
Characteristics of Teachers in Exemplary Model of
Early Reading Growth and Excellence (EMERGE)

and Control Classrooms

EMERGE Control
(n = 30) (n = 20)

Teacher Characteristics n % n %

Gender
Female 29 97 20 100
Male 1 3 0 0

Race/ethnicity
African American 18 60 11 55
Hispanic 3 10 3 15
White 8 27 4 20
Asian/other 1 3 2 10

Highest degree
Bachelor’s 13 43 8 40
Associate’s 11 37 8 40
High school 6 20 4 20

Total years of experience
1–5 0 0 3 15
6–10 8 27 8 40
11–15 10 33 4 20
16–20 6 20 2 10
20+ 6 20 3 15

Years in current position
1–5 9 30 6 30
6–10 7 23 8 40
11–15 8 27 3 15
16–20 6 17 2 10
20+ 1 3 1 5

208 Topics in Early Childhood Special Education

Although early childhood services based on RTI are
similar to school-age models, there are important differ-
ences in both the application and evaluation of an RTI
model for early intervention. Consistent with an RTI
approach, the foundation for EMERGE is universal imple-
mentation of Tier 1 instruction that provides literacy-rich
classroom environments and scientifically based early lit-
eracy practices for all children. The intervention tiers of
EMERGE incorporate a stronger focus and practice with
early literacy skills for small groups of selected children
who fall below peers based on progress-monitoring data
(Tier 2) and/or for individual children who evidence sig-
nificant delays based on screening and assessment mea-
sures (Tier 3). One difference between RTI for school-age
children and EMERGE relates to the content and strate-
gies for Tier 2 and Tier 3 instruction. In elementary and
secondary schools, there is often lack of consensus about
the precise nature of Tier 2 and Tier 3 interventions
(Fuchs & Fuchs, 2006). Most often, however, multiple
tiers are associated with interventions that are different

from Tier 1 or universal intervention. By contrast, in the
EMERGE program, all intervention tiers are structured
around a common core set of fundamental early literacy
skills (referred to as SOAP skills) for which there is fairly
strong consensus about their importance for later reading
success. Thus, rather than differentiating tiers on the basis
of the content or focus of specialized interventions, what
varies is the degree of explicit and individualized empha-
sis on SOAP skills.

Against this backdrop of uniformity in skills and abil-
ities that are critical for promoting early literacy devel-
opment is a philosophy of education that characterizes
early intervention, specifically, the importance of devel-
opmental appropriateness. Early childhood is a period of
sporadic, variable, and highly individual growth and devel-
opment. The practice guidelines and recommended prac-
tices of professional organizations, such as the National
Association for the Education of Young Children and the
Division of Early Childhood, reflect this philosophy and
emphasize the need for early education to be responsive

Table 2
Beginning and End-of-Year Performance on Literacy Measures for Exemplary Model of

Early Reading Growth and Excellence (EMERGE) and Control Children

EMERGE Control
(n = 188)b (n = 154)b

Outcome Measurea September May September May F Valuec

Peabody Picture Vocabulary Test–III 84.20 90.42 81.85 84.97 229.43
(r = .30–.56) (12.96) (11.51) (14.98) (17.25) p < .001, η2 = .45

Alphabet Knowledge 5.63 14.89 3.04 8.36 205.40
(r = .27–.55) (7.69) (7.47) (5.70) (8.43) p < .001, η2 = .44

Alliteration 3.42 5.05 3.20 4.00 13.42
(r = .29−.59) (2.15) (2.06) (2.67) (2.55) p < .001, η2 = .22

Rhyming 3.86 7.39 3.59 5.94 8.30
(r = .24–.59) (3.90) (3.73) (2.88) (4.42) p < .006, η2 = .13

Story Retelling 2.09 3.43 1.92 2.36 80.99
(r = .39–.50) (2.26) (1.41) (2.51) (2.30) p < .001, η2 = .34

Picture Naming 14.09 20.34 13.64 15.66 65.74
(r = .36–.51) (6.15) (5.87) (6.70) (6.75) p < .001, η2 = .20

Print Awareness 3.30 5.41 3.22 4.02 39.56
(r = .30–.56) (2.34) (2.04) (2.36) (2.63) p < .001, η2 = .28

Name Writing 2.54 4.35 2.17 3.95 33.84
(r = .24–.55) (2.83) (2.06) (1.87) (2.08) p < .001, η2 = .27

a. r indicates correlations with other measures.
b. The number of children varied slightly for each measure because of absences on the days of testing. When children were absent, test scores
were entered as missing data.
c. EMERGE versus control group differences in May, covarying for September performance.

Gettinger, Stoiber / Response-to-Intervention Model 209

to children’s developmental needs. When implementing
RTI with young children, a challenge arises when
attempting to apply uniform decision rules to determine
movement between intervention tiers. Operationalizing
the decision-making process, especially for Tier 2 inter-
vention, is problematic. In EMERGE, determining the
need for Tier 2 instruction blends teachers’ knowledge of
children’s progress gained through observations during
everyday Tier 1 learning experiences with more stan-
dardized performance data acquired through monthly
progress monitoring. Teachers are encouraged to incor-
porate their own impressions about how children are
responding to Tier 1 instruction in determining the need
for Tier 2 small-group instruction. Equally important in
this decision-making process is collaboration and con-
sultation with the early literacy coach who monitors the
implementation of Tier 1 instruction and environments
as well as children’s performances. In effect, movement
between intervention tiers in EMERGE is a more flexi-
ble and dynamic process than what characterizes RTI
with older children. This flexibility, while responsive to
the changing developmental needs of young children,
poses a challenge to researchers in attempting to system-
atically evaluate the tiered components of an RTI model.
For example, because movement between Tier 1 and Tier

2 is frequent (at least monthly), it is difficult to create a
comparison group of children who are at equivalent skill
levels. An effective RTI approach should reduce variance
in children’s performances; therefore, children may
move in and out of the lowest performing groups fre-
quently. Although comparison between EMERGE and
control classrooms on outcome measures is possible, it is
more difficult to extract a comparison group for children
who receive Tier 2 and Tier 3 intervention. In EMERGE,
we aim to conduct more frequent assessment of control
children in the next 2 years to be able to make these
appropriate comparisons.

In sum, the use of an RTI model with young children
is consistent with the increasing emphasis on early inter-
vention and scientifically based early literacy instruction.
The ongoing development of appropriate progress-
monitoring tools for young children, such as the IGDIs,
and the growing evidence base identifying important
early literacy skills have supported the development and
utility of an RTI model for early childhood education. As
demonstrated through the development and implementa-
tion of EMERGE, there are significant benefits to an RTI
approach for promoting early literacy development and
long-term reading success among low-income, high-risk
preschool children.

Appendix A
Shared Book Reading Activity Card

Farm Flu
By Teresa Bateman. Illustrated by Nadine Bernard Westcott

•

Choose 2-3 pages and read them several times. First, model by emphasizing the
rhymes (e.g., wellandspell). Next, let the child fill in the blank (e.g., leave out the
wordspell).

• Help children play with sounds by thinking of other words to complete rhymes in the
book.

• Tell the child that the sentences in the story are made up of different words. Have
the child count the number of words on various pages.

• Look at the pictures together and talk about all the different kinds of farm animals.
Ask children what sound each animal makes, or have them imitate the movements of
each animal.

• Talk about what it would be like to work as a farmer. Ask: What do you think a
farmer does all day? Would you like to be a farmer?

So
un

d
A

w
ar

en
es

s
O

ra
l L

an
gu

ag
e

210 Topics in Early Childhood Special Education

A
lp

ha
be

t
K

no
w

le
dg

• Ask the child to find all the upper- and lowercase Os (or any other letter) on each
page.

• Ask the child to notice how the words cow and plow look the same near the end.
You can cover up the first letters to make this more apparent.

• With other rhyming words, ask the child to find (point to) the letters that are the
same in the pairs of words and to name (identify) the letters.

• Ask where to begin reading and have them point to each word as you read it.
• Point out the word flu the first time you see it and have the child “read” it every time

it occurs in the text.
• Talk about the different parts of the book and where each is located (e.g., author,

illustrator, page numbers, words).

• guernsey: cow that gives milk. They came from an island called Guernsey, which is
near France.

• recuperate: get better after being sick. Ask about a time when children were sick.
• miracle: something amazing that happens. It was a miracle that the animals suddenly

got better. Ask: Has something amazing ever happened to you?

P
ri

nt
A

w
ar
en
es

s
V

oc
ab

ul
ar

Text Teacher-Child Interactions

Preview
• Page through the book and talk about the different types of animals. Their names

can then be reviewed as you read.
• Ask children to predict what the book will be about. Encourage them to look at the

pictures and talk about what the farm animals are doing.

Pages

1-2

• Ask: Where should I start to read on this page? [Allow response.] Say: I’m going
to start reading right here, and I’m going to go this way.

• Say: Let’s make up a sentence about farms using only words that start with the
letter F. (Farm friends frolic for fun.)

• Point to the picture of the farm. Ask: Where is the /f/ sound in farm? Is it at the
beginning or the end of the word?

Pages

5-6

• Say a pair of words that rhyme (cow and plow) and pairs that don’t rhyme (flu and
milk). Ask the child to pick out the words that rhyme.

• Say a pair of words that start with the same letter (milk and mom) and a pair that
doesn’t start with the same letter (flu and cow). Ask the child to pick the words that
start with the same letter.

Pages

9-10

• Ask: Have you seen a chicken before? Where? Did you know that chickens lay
eggs? Do you eat eggs?

• Say: Listen to these words: cock-a-doodle-doo and ka-choo. Can you hear how
they sound the same at the end? They rhyme. Other words sound like that, too.
Let’s think of some (boo, new, dew, few, moo, kangaroo, too).

Gettinger, Stoiber / Response-to-Intervention Model 211

Pages

13-14

• Look at these two words: piglets and tub. Which one is longer? How would we
check? (Count the letters.)

• Let’s play say it slow, say it fast. I’m going to say tub really slowly and you say it
back to me fast. Now let’s switch. Let’s try it with rub.

• Let’s clap the word turkey. How many beats or syllables do you think it has? Let’s
try it. Do you think turkey has more or fewer beats than tub? Let’s find out!

Pages

17-18

• sound. Can you think of

• es your mom do when you have the flu? What does it look like this boy is
doing?

Listen to these words: wild, wooly. They start with a /w/
any other words that also start with a W? (water, work).

• What sound do sheep make? Can you make the sound?
What do

Pages

20-21

•

ark, spider, stegosaurus, swan, squirrel). What noises do those
animals make?

• What animal makes each of these sounds?
I see two words on this page that start with the letter S. Can you find them? Let’s
say them together. Can you think of any other animals that start with the letter S?
(snake, skunk, sh

Appendix B
Tier 2 Theme-Related Small-Group Activity

Theme VI: Staying Well

Activity: It’s in the Bag! Week 2: 2/19–2/23

Topic of Week: nutrition and exercise Focus Letters: Vv (vegetable), Ee (exercise)

Purpose of activity:
To focus on alphabet knowledge and alliteration by matching food items to the letter they
begin with.
Primary SOAP skill: × Sound Awareness
Oral Language and Vocabulary

× Alphabet Knowledge
Print Awareness

Materials needed for the activity:
brown lunch bags with a letter printed on both sides
foods (or food containers) that begin with the letters printed on the bags
basket to hold food items

Steps for the teacher to prepare and implement the activity:
1.

with the same letter (e.g., popcorn and peach). Label the food items.
2.
3.

bags.
4.

sound of the first letter (if able to do so), and place it in the bag with the letter.

•

•
•

Collect foods that begin with various letters, including 3 to 5 pairs of items that start

Label each bag with the beginning letters of foods.
Place the food in the basket and line up the bags so children can see the letters on the

Tell children to select one food item, name the food, identify the first letter, say the

212 Topics in Early Childhood Special Education

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Variations or additions:
Use this activity to focus on alliteration. When there are two foods that start with the
same letter (and sound), take them out of the bag. Emphasize that the two foods start with
the same sound (e.g., popcorn and peach).
Take a food out of a different letter bag (e.g., carrot). Say all three foods (e.g., popcorn,
peach, carrot) and ask children to say the two foods that start with the same sound.
Math and science connections:
Count the number of foods in each bag. Determine which letter bag has the most, which
has the least. Graph results.
Talk about the different types of food groups—vegetables, dairy, grains, etc.

•
•
•
•

Gettinger, Stoiber / Response-to-Intervention Model 213

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Maribeth Gettinger is a professor in the School Psychology
Program, Department of Educational Psychology, at the University of
Wisconsin–Madison.

Karen Stoiber is a professor and program director in School Psychology,
Department of Educational Psychology, at the University of Wisconsin–
Milwaukee.

Early Head Start Relationships: Association
with Program Outcomes

James Elicker

Human Development and Family Studies, Purdue University

Xiaoli Wen

Early Childhood Education, National College of Education, National Louis University

Kyong-Ah Kwon

Department of Early Childhood Education, Georgia State University

Jill B. Sprague

Human Development and Family Studies, Purdue University

Research Findings: Interpersonal relationships among staff caregivers, parents, and children have
been recommended as essential aspects of early childhood intervention. This study explored the

associations of these relationships with program outcomes for children and parents in 3 Early Head

Start programs. A total of 71 children (8–35 months, M ¼ 20), their parents, and 33 program
caregivers participated. The results showed that caregiver–child relationships were moderately

positive, secure, and interactive and improved in quality over 6 months, whereas caregiver–parent

relationships were generally positive and temporally stable. Caregiver–child relationships were more

positive for girls, younger children, and those in home-visiting programs. Caregiver–parent relation-

ships were more positive when parents had higher education levels and when staff had more years of

experience, had more positive work environments, or had attained a Child Development Associate

credential or associate’s level of education rather than a 4-year academic degree. Hierarchical linear

modeling analysis suggested that the quality of the caregiver–parent relationship was a stronger

predictor of both child and parent outcomes than was the quality of the caregiver–child relationship.

There were also moderation effects: Stronger associations of caregiver–parent relationships with

observed positive parenting were seen in parents with lower education levels and when program

caregivers had higher levels of education. Practice or Policy: The results support the importance
of caregiver–family relationships in early intervention programs and suggest that staff need to be

prepared to build relationships with children and families in individualized ways. Limitations of this

study and implications for program improvements and future research are discussed.

Early Head Start is a federally funded community-based program for low-income families with

infants and toddlers and pregnant women, with goals to enhance child development and promote

healthy family functioning (Early Head Start National Resource Center, 2008). A guiding

Correspondence regarding this article should be addressed to James Elicker, PhD, Department of Human Development

& Family Studies, Purdue University, Fowler Memorial House, 1200 West State Street, West Lafayette, IN 47906-2055.

Early Education and Development, 24: 491–516

ISSN: 1040-9289 print/1556-6935 online

DOI: 10.1080/10409289.2012.695519

principle of Early Head Start is the importance of building positive relationships between program

caregivers and participating families in order to support positive change. Early Head Start advocates

that strong positive staff–family relationships that continue over time are key elements of a

high-quality program. More generally, in the literature, building positive staff–client relationships

has been recognized as an evidence-based best practice in early intervention programs targeting

high-risk young children and their families (e.g., Klass, 2003; Raikes & Edwards, 2009; Turnbull,

Turbiville, & Turnbull, 2000). These relationships include those among the child, the family, and

program caregivers, recognizing the parent–child bond as the child’s most significant relationship

(Lally & Keith, 1997).

Although building positive relationships is emphasized in the Early Head Start Performance

Standards (U.S. Department of Health and Human Services, 2002), in the National Association

for the Education of Young Children’s Developmentally Appropriate Practice in Early Child-
hood Programs (Copple & Bredekamp, 2009), and in the goals of many early intervention
programs, few studies have actually examined the association between dyadic interpersonal

program relationships and outcomes for children and parents. In this study we explored the qual-

ity of the interpersonal relationships among program caregivers, parents, and children in three

midwestern Early Head Start programs, with the goal of better understanding program relationships

and contributing data useful for improving services in Early Head Start and other relationship-based

early intervention programs. First, this study was intended to contribute new data about how infants’

and toddlers’ development proceeds in the context of relationships in Early Head Start. Second,

the study focused on describing program–family relationships: their nature and variation, how

they change over time, how they vary with program caregivers’ and families’ characteristics, and

whether they are associated with parent and child outcomes. These issues are critical for Early Head

Start, given that interpersonal relationships are viewed as a key component of program quality.

However, they have not been a primary focus of many studies, including the large-scale national

Early Head Start Research and Evaluation Project (Love et al., 2002).

MOTHER–CHILD ATTACHMENT RELATIONSHIPS: A FOUNDATION FOR
EARLY INTERVENTION

The early experience of a majority of young children today encompasses a network of inter-

personal relationships, both within and outside the family. The child development and infant

mental health literatures have converged on a relationship perspective to conceptualize early

social-emotional development (e.g., Cicchetti, Toth, & Lynch, 1995; Elicker & Fortner-Wood,

1995; Lyons-Ruth & Zeanah, 1993). This relationship-focused perspective is based on modern

attachment theory (Bowlby, 1973; Sroufe, 1983), which suggests that infants’ everyday inter-

actions with their primary caregivers result in strong emotional relational bonds. Depending

on the sensitivity and consistency of caregiving over time, attachment bonds vary in the amount

and quality of felt security conveyed to the infant. Another attachment postulate is that primary

relationships are mentally represented by even very young children. These representations, or

internal working models, subsequently guide children’s behavior in interpersonal relationships,

including relationships outside of the family, such as relationships with peers and teachers

(Elicker, Englund, & Sroufe, 1992). In this way, primary caregiving relationships, including

those with important nonparental caregivers, are expected to have an impact on children’s devel-

oping personalities, social competence, and other capacities.

492 ELICKER, WEN, KWON, SPRAGUE

Researchers using an attachment-relationships perspective have focused attention primarily

on the mother–infant relationship (e.g., Garcia Coll & Meyer, 1993; van IJzendoorn & Sagi,

1999). Many studies across several cultures have found consistent and strong associations

between mother–infant attachment security and children’s later social-emotional and cognitive

functioning (e.g., Crittenden & Claussen, 2000; Shonkoff & Phillips, 2000). Therefore, promot-

ing the parent–child attachment relationship has become a focus of many early intervention pro-

grams supporting children from high-risk backgrounds (Emde, Korfmacher, & Kubicek, 2000).

Guided by attachment theory and mother–child research, birth-to-3 practitioners have come to

view their relationships with children as focal aspects of successful early interventions and child

care programs, given the extensive amount of time that they have spent with the children (e.g.,

Ahnert, Pinquart, & Lamb, 2006; Howes, 1999; Lally et al., 2003).

NONPARENTAL CAREGIVER–CHILD RELATIONSHIPS: A GROWING
RESEARCH INTEREST

A growing body of research supports a general hypothesis that infants’ and toddlers’ relationships

with nonparental caregivers in early care and education settings affect socioemotional and cognitive

development in ways similar to, though perhaps not as strongly as, relationships with parents. Recent

research in infant and toddler child care has shown that teacher–child interactions and relationship

quality are linked both concurrently and predicatively with children’s social-emotional, language,

and cognitive outcomes (e.g., Hausfather, Toharia, LaRoche, & Engelsmann, 1997; National Insti-

tute of Child Health and Human Development Early Child Care Research Network [NICHD

ECCRN], 2000a, 2000b). Research underscores the key role of teacher sensitivity, responsive-

ness, and positive teacher–child relationships in supporting child development (e.g.,

Early

et al., 2007; Howes et al., 2008; LoCasale-Crouch et al., 2007; Mashburn, 2008). However, many

studies of teacher–child relationships have used only global assessments that have focused on tea-

chers’ relationships with the whole child care group, such as the Infant=Toddler Environment
Rating Scale–Revised (Harms, Cryer, & Clifford, 2003) and the Caregiver Interaction Scale

(CIS; Arnett, 1989) rather than the relational dynamics within specific caregiver–child pairs.

It cannot be determined from studies using classroom-level relationship assessments whether

children’s outcomes are specifically associated with the quality of dyadic teacher–child relation-
ships. Among the more focused measures for assessing dyadic relationships are those for

caregiver–child attachment security (e.g., using the Strange Situation, Ainsworth, Blehar,

Waters, & Wall, 1978; or the Attachment Q-Set, Waters, 1995) and composite summaries of

caregiver–child interactions (e.g., the Observational Record of the Caregiving Environment,

NICHD ECCRN, 1996). There is evidence that caregiver–child relationships, when assessed

using these dyadic measures, are associated with aspects of children’s cognitive, language,

and social-emotional functioning and growth. For example, Howes and colleagues found signi-

ficant concurrent associations between attachment security with child care providers and pre-

schoolers’ social competence (Howes, 1997; Howes & Smith, 1995). However, the strongest

evidence to date for the developmental influence of child care relationships comes from the

NICHD Study of Early Care, which found that cumulative positive dyadic caregiving during

the first 3 years was significantly associated with children’s school readiness, expressive

language, and receptive language at 3 years (NICHD ECCRN, 2000b). Based on best practice

EARLY HEAD START RELATIONSHIPS 493

recommendations, theoretical predictions, and the evidence summarized, we hypothesized that

dyadic relationship quality between Early Head Start program caregivers and infants and

toddlers would be concurrently associated with the children’s social and cognitive development.

PROGRAM CAREGIVER–PARENT RELATIONSHIPS: A NEGLECTED ARENA

Compared with the research on caregiver–child relationships discussed previously, even less

research attention has been focused to date on relationships that develop between parents and

professionals (the adult relationships) in the context of early childhood programs. This is despite

the fact that birth-to-3 practitioners often identify relationships with parents as central to the

success of early intervention, as we discovered in preliminary case study interviews with Early

Head Start program caregivers (Elicker, Magaňa, & Sketchley, 2000).

Belsky’s (1984) determinants of parenting model suggests that relationships and social support

provided to mothers by spouses or other adults result in more positive, responsive parenting of the

infant and ultimately in more positive child development outcomes. In the early intervention field,

relationships between program caregivers and parents have gained increasing attention as a factor

promoting healthy parent–child attachment (Hans & Korfmacher, 2002). These programs typi-

cally aim to influence a mother’s daily interactions with her infant and=or her internal working
model of attachment through not only providing modeling and information about parenting but

also fostering a supportive, relationship between the mother and the program staff (Emde et al.,

2000). These supportive adult relationships are believed to provide emotional security to the

parent, which promotes more positive ways of thinking and feeling about self, others, and rela-

tionships (e.g., Egeland & Erickson, 2003; Heinicke, Fineman, Ponce, & Guthrie, 2001; Juffer,

Bakermans-Kranenburg, & van IJzendoorn, 2007). Relationship-based interventions have been

successful in promoting positive changes in parental sensitivity, parenting behaviors, and

parent–child attachment relationships (Egeland, Weinfield, Bosquet, & Cheng, 2000).

Belsky’s parenting model and the success of relationship-based, parent-focused interventions

suggest a hypothesis that supportive Early Head Start staff–parent relationships will result in more

positive parenting and thus better developmental outcomes for both parents and children. How-

ever, only a few studies to date have empirically tested the associations between staff–parent

relationships and parent or child program outcomes. Data from the Nurse Home Visiting program

in Memphis demonstrated that mothers’ perceptions of empathy from program staff were signifi-

cantly associated with empathic attitudes the mothers had toward their children (Korfmacher,

Kitzman, & Olds, 1998). An evaluation of the University of California at Los Angeles Family

Development Project, a 2-year intervention for first-time mothers, revealed that mothers’ trust

in and ability to work with the program staff had a significant association with the mothers’ respon-

siveness to their children’s needs (Heinicke et al., 2000). In the current study, we hypothesized that

supportive program caregiver–parent relationships would be positively associated with both child

social and cognitive development and positive parenting in Early Head Start programs.

In summary, effective infant-toddler interventions can be viewed not only in terms of how

well they support children’s development and positive parenting but also in terms of how well

they build supportive staff–child and staff–parent relationships factors (Bernstein, 2002). Thus,

the intervention program is conceived as system of interdependent interpersonal relationships,

including children, parents, and program staff, producing an overall relational climate and

494 ELICKER, WEN, KWON, SPRAGUE

constituting a key intervention process (Bertacchi, 1996; Egeland et al., 2000; Emde et al., 2000;

Heinicke et al., 2000).

FACTORS IMPACTING PROGRAM RELATIONSHIPS

Which child, family, and program caregiver characteristics are associated with relationships

between program caregivers, parents, and children? Not many studies have specifically looked

into this question, which would inform intentional practice targeting specific participant groups.

There is some evidence that program staff characteristics are related to staff members’ ability

to connect with families. For example, caregivers with higher education or more early childhood

training provide higher quality care to young children (e.g., Webster-Stratton, Reid, &

Hammond, 2001; Whitebook, Sakai, & Howes, 2004). It is also hypothesized that ongoing train-

ing and relationship-based program support is crucial to service providers’ ability to engage and

retain families in early childhood intervention program and to build strong partnerships with

families (Jorde-Bloom, 2004; Parlakian, 2001; Wasik & Bryant, 2001). One study explicitly

compared the differences between nurse and paraprofessional home visitors (who did not have

advanced education and training) in terms of their program implementation and participant

outcomes in the Nurse Family Partnership program (Korfmacher, O’Brien, Hiatt, & Olds,

1999). The results showed that nurses and paraprofessionals did not differ in how participating

families rated the quality of their helping relationship. However, families visited by parapro-

fessionals tended to have less contact with the program and to drop out sooner. In the current

study, we hypothesized that program caregivers with higher education levels, more professional

training, and more program-related support would develop higher quality relationships with

Early Head Start children and parents.

Much evidence has shown that family risk (e.g., socioeconomic disadvantage, low education,

minority group status, high stress, and single parenthood) is among the factors that keep parents

from being involved (and building partnerships) and gaining benefits from intervention pro-

grams (e.g., Halpern, 2000; Robinson et al., 2002). Parents’ psychological characteristics

(e.g., depression) have also been related to families’ engagement in early intervention services.

For example, one study demonstrated that in a home visitation program, mothers with insecure

attachment relationship histories were less likely to engage with home visitors (Korfmacher,

Adam, Ogawa, & Egeland, 1997). Parents who had better interpersonal relationship skills more

readily formed collaborative relationships with intervention program staff (e.g., Brookes, Ispa,

Summers, Thornburg, & Lane, 2006). Other studies have shown similar patterns in how parti-

cipants’ psychological resources are associated with the way they use program services and

interact with staff (e.g., Florian, Mikulincer, & Bucholtz, 1995; Spieker, Solchany, McKenna,

DeKlyen, & Barnard, 2000). In the current study, we hypothesized that Early Head Start parents

with higher education levels and lower depressive symptoms would develop higher quality

relationships with both their own children and the Early Head Start program caregivers.

Finally, individual child characteristics might impact relationships with Early Head Start

caregivers. It has been reported that boys tend to demonstrate more negative interactions and rela-

tionships with mothers and teachers and generally have less optimal early school outcomes than

girls (Pianta & Walsh, 1996). There is also evidence that a child’s age may affect caregiver–child

relationship quality. For example, previous studies found that children who entered child care at

EARLY HEAD START RELATIONSHIPS 495

younger ages were more likely to have stable or secure relationships with caregivers than children

who entered child care at preschool age (Elicker, Fortner-Wood, & Noppe, 1999; Howes & Hamil-

ton, 1992). Similarly, the mother–child relationship is also affected by child age. One study

showed that mothers tended to display a lower level of warm responsiveness and a higher level

of restrictiveness as their infant approached toddlerhood (Smith, Landry, & Swank, 2000).

INTERACTIONS BETWEEN FAMILY AND PROGRAM FACTORS

These family and program factors not only may impact program relationships but could interact

with program relationships in predicting program outcomes. One of the challenges in evaluating

interventions with families at risk is the complexity of how family characteristics and program fac-

tors interact to produce program outcomes (Berlin, O’Neal, & Brooks-Gunn, 2003). In some pre-

vious intervention studies, family and program factors were considered as two separate contexts

rather than as interacting to produce program effects (Wen, Korfmacher, Hans, & Henson,

2010). In fact, there is some evidence that family and program factors (e.g., program relationships)

interact in rather complicated ways to predict program outcomes. For example, a prenatal and post-

partum support program with African American teen mothers found that the more program contact

mothers with limited vocabulary skills (a family factor) had with the home visitor (a program fac-

tor), the more likely they were to have positive birth experiences (Wen et al., 2010). However, very

few studies have investigated the interactions between family characteristics (e.g., maternal edu-
cation) and program context variables (e.g., program–family relationships). A goal of the current

study was to test for possible moderating effects of family and program caregiver characteristics on

associations between Early Head Start relationships and child and parent program outcomes.

RESEARCH QUESTIONS

The present exploratory study followed Early Head Start families and program caregivers over

a 6-month period to address the following research questions: (a) What is the nature of relation-

ships among Early Head Start program caregivers, children, and families, and how do these

relationships change over time? (b) What are the characteristics of the program, caregivers,

and families that are associated with Early Head Start relationship quality? (c) Are qualities

of these Early Head Start relationships associated with child and parent outcomes? (d) Do

characteristics of program caregivers and families moderate the associations between Early Head

Start relationships and child and parent program outcomes?

METHOD

Participants

A total of 71 parent–child dyads and 32 caregivers from three Early Head Start programs in

midwestern communities participated. Of the sample children, 52% were in the Early Head Start
home visitation program, which provided weekly home visits and targeted both parents and

child, and the rest were in an Early Head Start full-time center-based child care program that

496 ELICKER, WEN, KWON, SPRAGUE

mainly worked with the child. The average age of the child participants was 20 months, ranging

from 8 to 35 months. This age range is representative of the Early Head Start population. A total

of 42% of the children were boys. The majority of the children (69%) were White, 14% were
African American, and 10% were Hispanic. Children had been enrolled in Early Head Start
for an average of 14 months (SD ¼ 7.46) at the time of the study’s initial assessments.

Of the participating parents (mostly mothers), 84% had finished high school or had some
college education, 58% were married or living with a partner, 48% had a job at the time the study
began (average of 29 work hours per week), and 37% were in school or job training. Parents’
average age was 25 years, ranging from 17 to 40 years. All families were low income and lived

below the federal poverty income level and were therefore eligible for Early Head Start services.

Of the Early Head Start staff participants, 63% had a bachelor’s degree or higher, and 72% had
majored in early childhood education or child development or had taken relevant courses. The

majority of the staff (79%) was White. On average, the caregivers had worked with the program
for 2.4 years (SD ¼ 1.48, range ¼ 3 months to 6 years). The sample size of caregivers was evenly
distributed across the three participating Early Head Start programs (ns ¼ 10, 10, and 13). On
average, each caregiver worked with two children in the sample (34% worked with one child,
34% worked with two children, and 32% worked with more than two).

The participants were followed over a 6-month time period. For the follow-up assessments, 49

parent–child dyads (70% of the original sample; 45% were in the home visitation program) remained
available. The reasons for attrition involved participants moving out of the program service area,

dropping out the program, or having difficulty scheduling follow-up assessments before the child

graduated from the program. Many Early Head Start families’ living situations were in flux. Lack

of voicemail, changing phone numbers, relocating residence out of the area, and irregular work

schedules were among factors that prevented follow-up visits. The attrition rate found in this sample

is typical among studies that involve a Head Start population (e.g., Love et al., 2002). An attrition

analysis based on chi-square and t tests showed that in comparison with the original sample, the Time
2 sample had a lower proportion of parents without a high school diploma (10% vs. 16%) and a lower
proportion of parents living with a partner or spouse (55% vs. 58%). Otherwise, the Time 1 and Time
2 samples were not statistically different in terms of other demographic characteristics.

Procedure

Participants were recruited by solicitation at parent meetings and by distribution of flyers within the

three Early Head Start programs. The eligibility criteria were that the child had to be between 8 and

30 months old and have been enrolled in the program for at least 1 month. The study involved four

assessments, two at the initial time and two at the 6-month follow-up. Of the initial assessments, one

was conducted with the child and parent at home, and the other was conducted with the child and

Early Head Start program caregiver in the classroom or the child’s home (if the child was in the home

visitation program). The initial home assessment that involved the parent and child took about 2 hr

and was conducted during a time when the child was well rested and fed. The child was assessed

using a standardized developmental measure, the Mullen Scales of Early Learning, and a semistruc-

tured parent–child play interaction session was videotaped for 15 min. In addition, the parent was

asked to complete a survey regarding family demographic information, child development, depress-

ive symptoms, and the parent’s current relationship with the child’s primary Early Head Start care-

giver. For the second assessment, which involved the Early Head Start caregiver and the child, their

EARLY HEAD START RELATIONSHIPS 497

interactions were observed for 2 hr in the classroom (if the child was in a center-based program) or

during a home visit (if the child was in the home-based program). In addition, the Early Head Start

caregiver completed a survey describing his or her professional backgrounds, the child’s develop-

ment, and his or her relationship with the parent. The same measures and procedures were repeated

in the parent–child and caregiver–child 6-month follow-up assessments.

Overall, this study adopted a short-term longitudinal design to examine the nature and impact of

Early Head Start relationships. Although the participants had an average of 1 year of program

exposure at the beginning of the study, it was unclear whether their relationships with program care-

givers had stabilized or were still in the process of growing. There is a limited literature to guide

research regarding relationship development, in terms of formation and maintenance. Our working

hypothesis was that relationship building is a continuous process that may fluctuate over time,

especially in the context of interventions with children and families experiencing high-level life stress

and challenges. Considering documented evidence of Early Head Start participants’ overall low level

of program involvement (e.g., Love et al., 2002), we hypothesized that the relationships between pro-

gram caregivers and families would improve over the course of the study for participants who

remained in the program. In addition, a 6-month time period is a reasonable timeframe in which to

measure changes in infants, toddlers, and parents that might be related to their program experiences.

Measures

Relationship Quality

The quality of relationships between Early Head Start caregivers and children was assessed using

three observational measures in the classroom setting or during the home visit, and all of the

measures were appropriate for children aged 0–3. The quality of the relationship between Early

Head Start caregivers and parents was assessed using a parent and caregiver self-report scale.

Program caregiver–child relationships: attachment security. The Safe and Secure Scale
(Booth, Kelly, Spieker, & Zuckerman, 2003), a 15-item, 9-point scale derived from the Attach-

ment Q-Set (Waters, 1995), was used to describe the focus child’s secure base behavior toward

the Early Head Start caregivers (example item: ‘‘If child care provider reassures him by saying

‘It won’t hurt you,’ child will approach or play with things that initially made him cautious or

afraid’’: 1 ¼ very unlike this child, 5 ¼ neither like nor unlike this child, 9 ¼ most like this child).
The 15 scale items focus on the child’s ability to seek and receive positive attention, feel safe and

protected, receive support for exploration, receive consolation when distressed, and seek and

accept assistance. The scale has established reliability (a ¼ .81) and was positively correlated
with proximal measures of child care quality (Booth et al., 2003). The interobserver reliability

for the current study was established at 80% exact agreement.

Program caregiver–child relationships: level of involvement. The child’s interactive
involvement with his or her caregiver was rated using a slightly modified version of the Adult–Child

Involvement Rating Scale (Howes & Stewart, 1987). For each 20-s interval during eight equally

spaced, 15-min observation sessions, the highest level of interactive involvement between the child

and caregiver was scored. Scale points range from 0 to 6 (0 ¼ absent, adult not present; 1 ¼ ignores,
ignores, the adult ignored the child; 2 ¼ routine, if the caregiver touched the child for changing or other
routine caregiving but made no verbal responses to child; 3 ¼ minimal, if the caregiver touched the

498 ELICKER, WEN, KWON, SPRAGUE

child only for necessary discipline, to answer direct requests for help, or to give verbal directives with

no reply encouraged; 4 ¼ social, if the caregiver answered the child’s verbal bids but did not elaborate
or used some unnecessary positive physical contact; 5 ¼ elaborative, if the caregiver engaged in some
positive physical gestures, acknowledged the child’s statements and responded but did not restate the

child’s statement, sat with the child during play; and 6 ¼ intense, if the caregiver hugged or held the
child, restated the child’s statements, engaged the child in conversation, or played interactively with

the child). Summary scores were calculated as the mean level over the 2-hr observation period. The

scale has adequate test–retest reliability and is correlated with other relevant child care variables

(Howes & Smith, 1995). For the current study, an 80% exact agreement was attained between the
observers during two consecutive live observations.

Program caregiver–child relationships: positive caregiving. The CIS (Arnett, 1989) was
adapted to assess the interaction quality between Early Head Start caregivers and children. The scale

consisted of 26 items (e.g., ‘‘speaks warmly to the child,’’ ‘‘listens attentively when the children

speak to her’’) rated on a 4-point Likert scale (1 ¼ not at all, 2 ¼ somewhat, 3 ¼ quite a bit, and
4 ¼ very much). The measure consists of four subscales: positive interactions (10 items; warm and
developmentally appropriate behavior), punitiveness (8 items; hostility, harshness, and use of threat),

detachment (4 items; low involvement and disinterest), and permissiveness (4 items). The permissive-

ness subscale was dropped because it measures caregiving style rather than the nature of caregivers’

interactions with children. The scale has high internal consistency (a ¼ .81; Jaeger & Funk, 2001) and
was found to predict child language development and attachment security (Whitebook, Howes, &

Phillips, 1989). For the current study sample, the internal consistency reliability was slightly lower

(a ¼ .63). The mean score of the 22 items in the three subscales of positive interactions, punitiveness
(reversed), and detachment (reversed) was computed for analyses. Table 1 presents intercorrelations

TABLE 1

Correlations Among the Early Head Start Relationships

Variable 1 2 3 4 5

Time 1 (N ¼ 71)

Caregiver–child relationship

1. Attachment security — .39�� .55�� .08 .03
2. Child–caregiver involvement — .53�� .08 .02
3. Positive caregiving — .09 .02

Caregiver–parent relationship

4. Parent-rated relationship — .28�

5. Caregiver-rated relationship —

Time 2 (N ¼ 49)
Caregiver–child relationship

1. Attachment security — .49�� .74�� .17 .25
2. Child–caregiver involvement — .49�� .02 .08
3. Positive caregiving — .05 .14

Caregiver–parent relationship

4. Parent-rated relationship — .15

5. Caregiver-rated relationship —

�p < .05. ��p < .01.

EARLY HEAD START RELATIONSHIPS 499

among these measures and suggests that the three caregiver–child relationship measures were signifi-

cantly correlated at both Time 1 and Time 2 (rs ¼ .39–.74).

Program caregiver–parent relationships. The Parent–Caregiver Relationship Scale
(Elicker, Noppe, Noppe, & Fortner-Wood, 1997) is a measure with parallel forms that both

parents and Early Head Start program caregivers completed independently to assess their percep-

tions of relationship quality with each other. Items in the scale assess the factors level of

trust=confidence (e.g., ‘‘The caregiver is someone I can rely on’’), collaboration (e.g., ‘‘We talk
about problems right away’’), affiliation (e.g., ‘‘I am interested in the caregiver’s personal life’’),

and caring (e.g., ‘‘This parent is a caring person’’). The scale consists of 35 items scored on

a 5-point Likert scale (1 ¼ strongly disagree to 5 ¼ strongly agree). For the current sample,
the internal consistency reliability was .97 for the parent report and .96 for the program caregiver

report. Table 1 shows that correlations between parent and staff ratings were modest.

Child and Parent Outcomes

Early Head Start children’s social competence and cognitive abilities were assessed using

a naturalistic observation scale, parent and caregiver reports, and standardized assessments by

trained examiners, and the outcome measures aimed to look at the whole child’s development.

In addition, Early Head Start parents’ interactive parenting behaviors in a videorecorded home

play session were coded.

Child outcome: object play. A child’s level of play with objects, considered an indicator of
cognitive development, was rated using the scale developed by Rubenstein and Howes (1979)

during a 2-hr observation in the classroom or during a home visit. This 5-point scale rates the

complexity of the child’s object play from oral contact and passive holding to active mani-

pulation and exploration of the object’s unique properties for creative uses (1 ¼ oral contact,
2 ¼ passive, 3 ¼ active, 4 ¼ exploitative, and 5 ¼ creative). For each 20-s interval during eight
equally spaced, 15-min observation sessions, the highest level of play complexity was coded.

The mean level of object play over the 2-hr observation period was calculated. The scale has

adequate test–retest reliability and predicted other child development outcomes (Howes &

Smith, 1995). An interobserver reliability criterion of 80% exact agreement during two con-
secutive live observations was met by all observers prior to data collection.

Child outcome: social competence. Both the parents and Early Head Start caregivers
reported on the child’s emerging social competence and behavioral problems using the Brief

Infant–Toddler Social and Emotional Assessment (BITSEA; Briggs-Gowan & Carter, 2002).

The BITSEA includes 60 items, and each item is scored on a 3-point scale (0 ¼ not true=rarely,
arely, 1 ¼ somewhat true=sometimes, and 2 ¼ very true=often). The scale is composed of two
subscales—problem behaviors (49 items, such as hits, bites, or kicks the parent) and social
competence behaviors (11 items, such as paying attention for a long time)—and has established
reliability (range ¼ .66–.89) and validity (Briggs-Gowan, Carter, Skuban, & Horwitz, 2001). In
the current study, a composite score was created by combining social competence and reversed

problem behavior item raw scores into a total score representing overall socioemotional com-

petence (with a higher score representing greater competence). Internal consistency reliabilities

for parent and caregiver reports were .80 and .69, respectively. Because parent and caregiver

500 ELICKER, WEN, KWON, SPRAGUE

reports were not highly correlated at either time point (rs ¼ .48 and .19 at Time 1 and Time 2,
respectively), scores were computed separately for parent and caregiver BITSEA social-

emotional adjustment.

Child outcome: cognitive skills. The Mullen Scales of Early Learning, American
Guidance Services edition (Mullen, 1995) is an individually administered developmental test

that can be used with children from birth to 68 months. The participating children were admini-

strated the test during both initial and follow-up assessments. The assessment consists of four

cognitive scales (visual reception, receptive language, expressive language, and fine motor)

plus one gross motor scale. Scores on the four cognitive scales are combined to yield an Early

Learning Composite score, which, according to Mullen (1995) is an indicator of general intel-

lectual competence, with a mean of 100 and a standard deviation of 15. The internal consistency

reliabilities for the five subscales were reported to range from .75 to .83, and the interrater

reliabilities ranged from .91 to .99 for age groups between 1 and 44 months. The concurrent

validity of the measure has been supported by its correlations with other early development

measures (e.g., the Bayley Mental Development Index, rs ¼ .53–.59; the Preschool Language
Assessment Auditory Comprehension, r ¼ .85; Mullen, 1995).
Parent outcome: responsive parenting behaviors. Six responsive parenting

behaviors

were coded from the videotaped parent–child play interactions in the home setting using the

Three Bag Coding Scales (NICHD ECCRN, 1999). sensitivity (how the parent observes and

responds to the child’s cues), intrusiveness (the degree to which the parent controls the child,

rather than respecting his or her perspective), stimulation of cognitive development (the parent’s

effortful teaching to enhance perceptual, cognitive, and linguistic development), positive regard

(parent’s expression of love, respect, and admiration for the child), negative regard (parent’s

expression of discontent with, anger toward, disapproval of, and rejection of the child), and

detachment (parent’s lack of awareness of, attention to, and engagement with the child). Each

behavior was rated on a 7-point scale (1 ¼ a very low incidence of the behavior, 7 ¼ a very high
incidence of the behavior). The interrater reliability on each scale was established at 90% exact
agreement or better. Because all six parenting behaviors were positively intercorrelated at both

data collection points (bivariate rs ranging from .36 to .83), a composite score representing
overall responsive parenting behaviors was computed for both Time 1 and Time 2 by summing

the six individual behavior scores (negative parenting behavior scores were reversed). For the

current sample, the internal consistency for the six parenting behaviors was .91.

Participant Characteristics

Participant demographic characteristics and program information were collected through the

parent and caregiver surveys. In addition, parental depressive symptoms were assessed using the

Center for Epidemiological Studies–Depression scale (Radloff, 1977), a 20-item, 4-point scale

(example items: ‘‘I thought my life had been a failure’’, or ‘‘I felt fearful’’: 0 ¼ rarely or none
of the time, 3 ¼ all of the time). Higher scores reflect greater depressive symptoms.

Early Head Start program caregivers also completed the Early Childhood Work Environment

Survey (Jorde-Bloom, 1988), designed for early childhood care administrators, teachers, or

support staff for assessing dimensions of organizational climate (e.g., peer cohesion, support

for professional and personal growth, and the presence of facilitative leadership). The survey

EARLY HEAD START RELATIONSHIPS 501

consists of 75 items, with 10 items rated on 5-point Likert scales and the rest rated on dichot-

omous scales (yes vs. no). The scale has adequate reliability and validity and has been used in

several studies assessing early childhood program work environments (e.g., Jorde-Bloom, 1999).

RESULTS

This study explored questions regarding the nature of Early Head Start relationships, how they

change over time, their association with short-term child and parent program outcomes,

how family and program characteristics are associated with relationships, and how these charac-

teristics moderate the associations between Early Head Start relationships and program

outcomes. The following sections are organized to present results answering these questions.

What is the Nature of Early Head Start Relationships, and How Do They Change
over Time?

Table 2 summarizes the data on relationship quality among Early Head Start caregivers and part-

icipants at the two assessment points, disaggregated by program type (center-based vs.

home-based programs). Attachment security between children and their program caregivers

was observed at a moderate level of quality (between 5 and 6 on the 9-point scale) at both Time

1 and Time 2 and in both programs, with a relatively large degree of variance. Similarly, mean

levels of children’s interactive involvement with caregivers were low to moderate (between

TABLE 2

Early Head Start Relationships and Outcomes: Descriptive Statistics

Center-Based program Home-Based program

Time 1 (N ¼ 34) Time 2 (N ¼ 27) Time 1 (N ¼ 37) Time 2 (N ¼ 22)

Variable M SD M SD M SD M SD

Caregiver–child relationship

Attachment security
a

5.11 0.79 6.03 1.04 5.16 0.87 5.75 1.19

Child–caregiver involvement
b

2.52 0.87 3.31 0.71 3.27 0.86 3.59 0.47

Positive caregiving
c

3.10 0.27 3.49 0.30 3.28 0.24 3.44 0.36

Caregiver–parent relationship
d

Parent-rated relationship 4.22 0.45 4.17 0.72 4.01 0.76 4.00

0.66

Caregiver-rated relationship 4.11 0.57 3.95 0.55 3.94 0.62 3.82 0.65

Program outcomes

Object play 2.40 0.51 2.70 0.50 2.55 0.50 2.71 0.59

Early learning (Mullen) 104.59 15.13 103.52 16.01 100.05 16.92 94.45 17.96

Parent-rated BITSEA 0.99 7.34 4.33 7.57 �1.15 11.23 �2.49 12.63
Caregiver-rated BITSEA 4.25 9.89 2.82 12.38 2.47 12.23 2.29 12.40

Parenting behavior 32.12 4.42 33.52 3.23 29.67 6.05 30.59 6.11

Note. BITSEA ¼ Brief Infant–Toddler Social and Emotional Assessment.
a
Attachment security was assessed on a 9-point scale.

b
Child–caregiver involvement was assessed on 6-point scale.

c
Positive caregiving was assessed on 4-point scale.
d
Caregiver–parent relationship was assessed on a 5-point scale.

502 ELICKER, WEN, KWON, SPRAGUE

‘‘routine’’ and ‘‘minimal’’ at Time 1 and between ‘‘minimal’’ and ‘‘social’’ at Time 2). The

program caregivers displayed overall a high level of positive caregiving toward the group, as

measured by the CIS scale at both assessment points. Overall, the results suggested moderately

positive relationship quality between Early Head Start caregivers and children. As for adult

relationship quality, both program caregivers and parents rated their relationships quite posi-

tively (means were greater than 4 on the 5-point scale for parents and approaching 4 for care-

giver ratings), although program caregivers’ perceptions were slightly less positive than parents’.

A multivariate general linear model test was performed to examine whether the Early Head

Start relationships changed over the observed 6-month time period. The test (Roy’s largest root)

showed that there was an overall positive change in the Early Head Start relationships from the

Time 1 to Time 2 assessments, F(5, 43) ¼ 5.99, p ¼ .00. The univariate statistics indicated that the
three relationship measures that assessed Early Head Start caregivers and children had statistically

significant positive changes over time (ps < .01); however, the adult relationship ratings from program caregivers and parents did not change significantly across this 6-month period (p > .24).

What Are the Characteristics of the Program, Caregivers, and Families
that Are Associated with Early Head Start Relationship Quality?

The associations between participant characteristics and Early Head Start relationships were

examined using the full sample at the Time 1 assessment, allowing for a more extensive analysis

of these factors. The program and participant characteristics included in this analysis were child

age, gender, and ethnicity; parent education and depression; program caregiver work experience,

education, and perceptions of the work environment; and program service delivery model

(center-based child care vs. home visitation). Pearson correlations were conducted with con-

tinuous family and program characteristic variables (i.e., child age, parent depression, program

caregiver work experience, and perceptions of the work environment). Analysis of variance was

conducted with the discrete variables (i.e., child gender, ethnicity, parent education, program

caregiver education, and program service delivery model).

Analyses of variance showed that girls had more secure relationships than boys with their

center-based caregivers and home visitors (Safe and Secure Scale; Ms ¼ 5.30 and 4.90 for girls
and boys, respectively), F(1, 69) ¼ 4.26, p < .05. Children in the home-based program were observed as showing a higher level of interactive involvement with program caregivers than

children in the center-based program (Ms ¼ 3.27 and 2.52, respectively), F(1, 69) ¼ 13.48,
p < .01. And caregivers in the home-based program displayed a higher level of positive caregiving as measured by the CIS than those in the center-based program (Ms ¼ 3.28 and 3.10, respectively), F(1, 69) ¼ 8.93, p < .01. Child ethnicity and caregiver education level were not significantly associated with any of the three caregiver–child relationship measures.

As for the caregiver–parent relationships, program caregivers reported more positive relation-

ships with parents who had higher levels of education (Ms ¼ 4.13 and 3.62 for parents who had
finished high school and parents who had not, respectively), F(1, 69) ¼ 7.53, p < .01. However, parents reported better relationship quality with program caregivers who had lower education levels (Ms ¼ 4.31 vs. 3.99 for caregivers who had an associate’s degree and ones who had a bachelor’s degree or higher, respectively), F(1, 69) ¼ 4.66, p < .05. Adult relationship quality was not different for the two program service delivery models.

EARLY HEAD START RELATIONSHIPS 503

Table 3 presents correlations among the continuous measures of participant characteristics

and the Early Head Start relationships. Younger children tended to display higher attachment

security and experienced more positive interactions with program caregivers (as measured by

the CIS). Caregivers who had more years of work experience demonstrated higher levels of

interactive involvement with children; those who had more positive perceptions about their Early

Head Start program work environment reported more positive relationships with the parents.

Parental depressive symptoms were not significantly related to any of the relationship measures.

Are Early Head Start Relationships Associated with Child and Parent Outcomes?

Table 2 presents descriptive statistics for the child and parent program outcome measures at

the two assessment points, disaggregated by the program type (center-based vs. home-based

program). The paired samples t tests showed that children’s object play (t ¼ �2.41, p ¼ .02)
and parenting behaviors (t ¼ �2.90, p ¼ .006) had significant gains over the 6-month period,
whereas the other three child outcomes did not show significant changes.

The associations between Early Head Start relationships and program outcomes were

analyzed through hierarchical linear modeling (HLM; Raudenbush & Bryk, 2002) because of

the nested nature of the data. The sample children were nested within three different centers,

two different program models (center-based vs. home-based programs), and 32 Early Head Start

caregivers. However, multilevel modeling could not be performed at the level of the center or

program type because these higher group-level samples were too small. They were, however,

included as dummy-coded covariates. The study involved 32 program caregivers, and on

average, each caregiver worked with two children in the sample (34% worked with one child,
34% worked with two children, and 32% worked with more than two). Therefore, it was appro-
priate to conduct multilevel analysis at the caregiver level. The methodology literature suggested

that even though this Level 2 caregiver sample was relatively small, the analysis would allow for

precise estimations (Maas & Hox, 2005; Snijders & Bosker, 1999). However, because of the

overall small sample in this study and the degree of data attrition over time, the HLM analysis

could be conducted only with the Time 1 full sample (n ¼ 71), not with the Time 2 sample
(n ¼ 49). These analysis decisions were guided by general principles of sample size for HLM

TABLE 3

Correlations Between Participant Characteristics and Early Head Start Relationships (N ¼ 71)

Variable Child age

Caregiver work

experience

Caregiver-Rated work

environment Parent depression

Caregiver–child relationship

Attachment security �.32�� .11 �.12 �.22
Child–caregiver involvement �.03 .30� �.06 .10
Positive caregiving �.25� .03 �.07 �.001

Caregiver–parent relationship

Parent-rated relationship �.10 .27 .08 �.15
Caregiver-rated relationship .06 .04 .44�� .23

�p < .05. ��p < .01.

504 ELICKER, WEN, KWON, SPRAGUE

analysis (Tabachnick & Fidell, 2006). Because of the sample size limitations of the study, it was

necessary to reduce the number of variables included in the analysis. Given the fact that the

Early Head Start caregiver–child relationship measures were significantly correlated (see

Table 1), a composite score (computed by standardizing each measure and then summing the

weighted units) was used to represent overall caregiver–child relationship quality. Similarly,

a composite score for overall caregiver–parent relationship quality was computed by averaging

the total scores of the parents’ and Early Head Start caregivers’ ratings. Although the parent and

caregiver ratings were only modestly correlated, this composite score took into account the

perspectives of both parties. The resulting caregiver–child and caregiver–parent relationship

composite scores were not significantly correlated, r(71) ¼ .04, p > .05.
Two-level HLM analyses were performed to predict each child and parent outcome. Analyses

were conducted in two steps. The first step was to examine unconditional models that did

not include any covariates, only the intercept. Next two-level contextual models were estimated

that included the child and family covariates and relationship variables as Level 1 predictors and

caregiver-level covariates as Level 2 predictors. The Level 1 covariates included the caregiver–

child and caregiver–parent relationship variables, child age, child gender, parent education,

parent depression, and program type (center-based child care vs. home visitation; dummy

coded). These predictors were significantly correlated with one or more outcomes in the prelimi-

nary analysis. The Level 2 covariates included the program caregivers’ work experience and

education level. Preliminary analyses suggested weak correlations among all of the covariates.

Only the caregiver–child relationship composite was inversely and modestly correlated with

child age (r ¼ �.25). Therefore, concern about collinearity was allayed.
The models were computed in HLM 6.06 and estimated using full maximum likelihood. Both

Level 1 and Level 2 covariates were grand-mean-centered (given the small n per caregiver). The
Level 2 intercept was modeled as randomly varying. The contextual model was as follows:

The Level 1 model was:

Yij ¼ b0j þ b
�

1j ðPROGRAMijÞ þ b
�

2j ðP EDUijÞ
þ b �3j ðDEPRESSIONijÞ þ b

�
4j ðCHILDSEXijÞ þ b

�
5j ðCHILDAGEijÞ

þ b �6j ðSC RELATIONijÞ þ b
�

7j ðSP RELATIONijÞ þ rij
The Level 2 model was:

b0j ¼ c00 þ c �01 ðCAREGIVER EXPERIENCEjÞ þ c
�

02 ðCAREGIVER EDUjÞ þ u0j
b1j ¼ c10
b2j ¼ c20
b3j ¼ c30
b4j ¼ c40
b5j ¼ c50
b6j ¼ c60
b7j ¼ c70

The two Level 2 covariates were included to predict the intercept from the Level 1 model.

EARLY HEAD START RELATIONSHIPS 505

The unconditional model indicated that the proportion of variance in child=parent outcomes
between Early Head Start caregivers (intraclass correlation coefficient).ranged from about 1%
to 27% (object play, 27%; early learning, 6%; parent-rated social competence, 2%; caregiver-
rated social competence, 1%; and parenting behaviors, 18%). Therefore, a larger proportion
of variance resided within children and parents.

Results of the contextual HLM model are presented in Table 4. For the statistically significant

coefficients, effect sizes were calculated as ðB�XSDXÞ=SDY, where SDY represents the variance
term for the intercept at the level at which X centers in the model. Effect sizes are, therefore,

interpreted as expected change in standard deviation units in Y that is associated with

a standard deviation change in X. The caregiver–child relationship quality composite was not

related to any of the child or parent outcomes at the initial assessment after child, parent, and

TABLE 4

Association Between Early Head Start Relationships and Program Outcomes (N ¼ 71)

Variable

Object

play

Early

learning

Parent-Rated

BITSEA

Caregiver-Rated

BITSEA

Parenting

behaviors

Fixed effects, coefficient (SE)

Intercept (c00) 2.50
��

(0.06)

102.12��

(1.97)

�0.06
(1.03)

3.07�

(1.29)

30.58��

(0.76)

Caregiver work experience (c01) �

0.02

(0.05)

�1.44
(1.48)

�1.28
(0.79)

0.12

(0.99)

�0.22
(0.54)

Caregiver education: bachelor’s

or higher (c02)
a

�

0.11

(0.16)

�0.42
(5.05)

�1.56
(2.68)

4.46

(3.35)

0.66

(1.87)

Program type: home-based

program (c10)
b

0.05

(0.16)

�0.63
(5.02)

�1.21
(2.69)

�1.07
(3.36)

�1.09
(1.78)

Parent education: high school

or higher (c20)
c

0.03

(0.15)

9.39

(5.31)

�0.28
(3.04)

5.34

(3.80)

2.08

(1.39)

Parent depression (c30) 0.003

(0.01)

0.02

(0.23)

�0.11
(0.13)

�0.02
(0.16)

0.11

(0.07)

Child gender: female (c40)
d �0.23�

(0.11)

3.36

(3.88)

3.24

(2.20)

5.08

(2.75)

2.36�

(1.07)

Child age (c50) 0.03
��

(0.01)

�

0.09

(0.27)

0.25

(0.15)

0.10

(0.19)

0.23��

(0.08)

Caregiver–child relationship

composite (c60)
0.04

(0.03)

�0.40
(0.88)

0.37

(0.49)

�0.61
(0.61)

�0.55
(0.29)

Caregiver–parent relationship

composite (c70)
�0.25�
(0.12)

11.97��

(4.09)

7.86��

(2.28)

5.27

(2.85)

4.73��

(1.16)

Random effects (variance

components)

Level 1 variance (r) 0.17 220.29 73.81 115.45 13.88

Intercept (u0), variance [v
2
, p] 0.04

[39.12, .10]

16.95

[33.61, .25]

0.09

[21.16, >.50]

0.14

[21.21, <.05]

10.12

[65.53, <.001]

Note. BITSEA ¼ Brief Infant–Toddler Social and Emotional Assessment.
a
Reference category is high school, Child Development Associate credential, or associate’s degree.

b
Reference category is center-based program.

c
Reference category is no high school diploma or general equivalency diploma.
d
Reference category is male.

�p < .05. ��p < .01. ��p < .001.

506 ELICKER, WEN, KWON, SPRAGUE

program characteristics were controlled. However, caregiver–parent relationship quality was sig-

nificantly associated with three child outcomes—object play (effect size ¼ �0.73, p ¼ .04), early
learning composite (effect size ¼ 0.03, p ¼ .01), and parent-rated social competence (BITSEA;
effect size ¼ 0.05, p ¼ .006)—although the association with children’s level of object play
was in an unexpected direction. Caregiver–parent relationship quality was also significantly

associated with observed positive parenting behaviors (effect size ¼ 0.17, p < .001). Girls displayed lower levels of object play compared with boys (effect size ¼ �0.67, p ¼ .04), but girls received more positive parenting from their parents than did boys (effect size ¼ 0.08, p ¼ .04). Child age was positively associated with level of object play (effect size ¼ 1.32, p ¼ .002) and parenting behaviors (effect size ¼ 0.12, p ¼ .007).

Do Characteristics of Program Caregivers and Families Moderate the Links Between
Early Head Start Relationships and Child and Parent Program Outcomes?

Given the limited sample size, only three family and caregiver characteristics of interest were

included as potential moderators: child gender, parent education level, and Early Head Start

caregiver education level. Full data collected at the initial assessment were again used for this

analysis. HLM analyses were run by including one outcome as the dependent variable,

a moderator variable (dummy coded), a relationship composite variable (grand mean centered),

and an interaction term between the moderator and the relationship variable (also grand mean

centered) as the independent variables. Child gender and parent education were included as

Level 1 variables, and Early Head Start caregiver education was included as a Level 2 variable.

If the interaction term is significant, it indicates that the family or program caregiver charac-

teristic variable moderates the association between the relationship quality and the outcome vari-

able. To further explore a significant moderation effect, the association between the relationship

quality variable and the outcome measure was examined within two subsample groups formed

based on the moderators (i.e., with and without high school diploma based on parent education;

girls and boys based on child gender). This analytic strategy for examining and interpreting

moderation effects is based on recommendations by Aiken and West (1991). Graphic plots of

the moderation effects and the simple slope computation (predicting effects of the relationship

variable) for each subgroup were constructed using Mod-Graph software (Jose, 2008).

Two significant moderation effects were found, and they are displayed in Figures 1 and 2,

where the x-axis represents the caregiver–parent relationship quality composite and the y-axis

represents the level of observed positive parenting behaviors (total score). As shown in

Figure 1, the association between caregiver–parent relationship quality and observed responsive

parenting behaviors was moderated by parent education. The interaction between parent edu-

cation and the caregiver–parent relationship was found to be significant (b ¼ �5.56, p ¼ .03;
effect size ¼ �0.05). A stronger association between observed positive parenting behaviors
and caregiver–parent relationship quality was seen in parents who did not finish high school.

This association was weaker among parents who had a high school diploma or more education.

Another significant interaction was found with Early Head Start caregivers’ education level

and the quality of the parent–caregiver relationships (b ¼ 7.68, p ¼ .006; effect size ¼ 0.57).
As indicated in Figure 2, Early Head Start caregivers’ education level moderated the association

between the quality of parent–caregiver relationships and observed positive parenting behavior,

such that families who worked with program caregivers holding a bachelor’s degree or higher

EARLY HEAD START RELATIONSHIPS 507

FIGURE 1 Moderation effect by parent education. Parent education moderates the association between Early Head Start

caregiver–parent relationships and the observed responsive parenting behaviors.

FIGURE 2 Moderation effect by program caregiver education. Early Head Start caregivers’ education moderates the

association between caregiver–parent relationships and the observed responsive parenting behaviors.

508 ELICKER, WEN, KWON, SPRAGUE

displayed more positive parenting when their relationships with the Early Head Start caregiver or

home visitor were more positive. However, this association was not observed among families

working with program caregivers with lower degrees. Child gender did not show any moderating

effects on associations between the Early Head Start relationships and child or parent outcomes.

DISCUSSION

This study of the interpersonal relationships among parents, children, and program caregivers in

three midwestern Early Head Start programs contributes new insights, in terms of both theory

and application. Though the sample was relatively small, including 71 child–parent–caregiver

triads, the study included intensive observations and assessments over a 6-month period. Using

relatively new measures, we described the nature and variation of relationships children and

parents had with Early Head Start program staff. We identified factors that were associated with

more or less positive Early Head Start program relationships, and we found that positive and

supportive relationships, especially those between parents and program caregivers, predicted

positive outcomes for both parents and children.

For the Early Head Start children, we found that caregiver–child relationships varied but were

generally positive in terms of attachment security, interactive involvement, and positive care-

giving and that these relationships became increasingly positive over the 6-month period of

our observations. This suggests that given time, Early Head Start caregivers will develop more

positive and secure relationships with children. Such a continuity of care hypothesis is consistent

with current recommendations and some previous research emphasizing more time and conti-

nuity as key factors for nonparental caregivers to develop supportive relationships with young

children (e.g., Elicker et al., 1999; Howes & Hamilton, 1992; Lally, 2009).

Caregiver–parent relationships were uniformly positive in these Early Head Start programs

based on both parties’ reports. Parents’ perceptions were somewhat more positive, with less

variation, than ratings by program caregivers, a finding consistent with previous research

(Elicker et al., 1997; Green, McAllister, & Tarte, 2004; Korfmacher, Green, Spellmann, &

Thornburg, 2007; Roggman, Boyce, Cook, & Jump, 2001; Wen & Elicker, 2012). Although

Early Head Start caregivers’ evaluations tended to be positive, their relatively lower ratings

could be due to the fact that they hold higher standards for what an optimal relationship with

parents is like. Caregivers’ relationship assessments are made in the context of work with many

parents, therefore their evaluations may be more discerning and more variable across parents,

whereas parents have limited experience in relationships with program caregivers. These are

possibilities that should be explored in future research. Given the generally high ratings, it

was not surprising to find that relationships did not increase in quality over time, probably

reflecting a ceiling effect. Future research may want to use measures of caregiver–parent

relationships that capture a broader range of variation in relationship perceptions.

What characteristics of children, parents, or program caregivers predicted positive relation-

ships? We found that Early Head Start caregivers were more likely to have positive, secure rela-

tionships with girls and with younger children (infants) compared with boys and older children

(toddlers). It may be that boys and toddlers present challenges for caregivers striving to develop

positive relationships with them, as boys may be more active and less verbal, and toddlers are

more likely than infants to attempt to gain independence and autonomy, sometimes reacting with

EARLY HEAD START RELATIONSHIPS 509

resistance (e.g., Smith et al., 2000). Girls have been observed in other research to have more

secure attachment relationships with child care providers than boys (Ahnert et al., 2006). These

findings are also consistent with available evidence about parent–toddler relationships (e.g.,

Schoppe-Sullivan et al., 2006) and suggest a need for increased attention in Early Head Start

staff training to the process of building positive relationships with toddlers and with boys.

Children in the home-based program showed higher levels of interactive involvement with their

Early Head Start caregivers, and home-based caregivers displayed more positive caregiving than the

center-based caregivers. This is probably related to the fact that in home visiting, the program

caregiver focuses on one individual child and the parent intensively, usually for 3 hr one time

per week, and therefore is better able to spend quality time with the child and be attentive to the

child’s needs. In classroom settings, caregivers work with a small group all day every day, typically

four to eight children, including the focal child that we were observing. Therefore, this difference

in observed interactive involvement between the center-based and home-based samples (less

frequent=more intense vs. more frequent=less intense) is probably due to the distinctive context
for caregiver–child interaction that each of these program service delivery models presents.

Caregivers who rated their program work environment as more supportive, and those who

had attained a Child Development Associate credential or associate’s degree, tended to have

more positive relationships with parents than those who reported more negative views of their

work environment or those with higher levels of education. These findings support the impor-

tance of a positive and supportive work environment for caregivers in relationship-focused

programs like Early Head Start (Bertacchi, 1996; Jorde-Bloom, 2004). The results also suggest

that there may be special challenges for caregivers with more advanced levels of education to

develop trust, open communication, and feelings of collaboration with intervention families. It

could be beneficial in future research to examine more closely how and whether staff education

level makes a difference in the interactions and relationships that develop between program care-

givers and parents. Better educated, sometimes less experienced caregivers, when working with

parents with lower incomes and education levels, may feel unprepared, threatened, or mistrustful

in their interactions with those parents. However, caregivers with more similar backgrounds to

the parents’ backgrounds might be more comfortable balancing power and trust in their relation-

ships with parents. In fact, similarity in background with families has been a rationale for hiring

community members as paraprofessionals in some early intervention and family support

programs (Behnke & Hans, 2002; Hans & Korfmacher, 2002). We do not think these results

necessarily imply that advanced education needs to be an impediment for program caregivers

in establishing positive relationships with families. In fact, the results also showed that relation-

ship quality with parents was most strongly associated with positive parenting outcomes when

program caregivers had higher education levels. An important task for future inquiry should be

to determine how to provide preservice education, in-service training, and technical support for

professional caregivers to enable them to utilize their knowledge to effectively understand and

support parents and children in Early Head Start and similar programs serving families at risk.

Contrary to our hypothesis, the quality of caregiver–child relationships did not predict current

or future levels of children’s cognitive or social development. However, we did find that the

quality of caregiver–parent relationships was associated with concurrent measures of children’s

object play, social competence, early learning, and positive parenting. There are a number of

plausible explanations for these links. Supportive staff relationships with parents, with a focus

on the child’s development, may be a key part of an effective intervention for positive change

510 ELICKER, WEN, KWON, SPRAGUE

in both parents and children, a hypothesis that has been supported by results of randomized

studies (e.g., Heinicke et al., 2000; Roggman, Boyce, & Cook, 2009). The findings of the current

study contribute further evidence, though we cannot draw causal conclusions, given the correla-

tional design of the study.

The obtained inverse association between the quality of program caregiver–parent relation-

ships and children’s complexity of object play was counter to our expectations. A possibility that

bears further investigation is that children whose parents are more positively engaged with pro-

gram caregivers (and perhaps other adults) are also socially oriented and less likely to engage in

more complex play with objects at this age and in this observation context. Our finding that there

were no significant associations between the quality of caregiver–child relationships and child

outcomes was also unexpected and not consistent with previous research (e.g., NICHD ECCRN,

2000b). It is possible that this particular age (around 20 months) and this study’s short, 6-month

observation period, coupled with the relatively small sample, did not enable us to detect

influences of program caregiver–child relationships that may be modest, compared with the par-

enting influences. Our results did show that caregiver–child relationships improved over time.

However, our longitudinal analysis focused on the effects of initial relationship quality (using

the Time 1 sample), primarily because of sample size limitations. More extended longitudinal

studies with larger samples and repeated measures of both relationships and child outcomes

would enhance understanding of the influences of program caregiver–child relationships. It

may also be that normal developmental changes or other influences (especially family influ-

ences) at this age overshadow the influences of program relationships on children’s development

(e.g., Downer & Pianta, 2006; NICHD ECCRN & Duncan, 2003).

The discovery of family and caregiver characteristics that were moderating influences help

us better understand potential associations between relationships and program outcomes. One

moderation effect suggests that parents with lower education levels are more likely to exhibit

positive parenting in a play session with their child when they have more positive relationships

with their child’s program caregivers, whereas the parenting of those with higher education

levels was less strongly linked to the quality of this adult relationship. A plausible interpretation

is that supportive relationships with program caregivers are especially important in supporting

positive parenting in parents with lower education levels. Relationships with a caring and

supportive professional may provide both emotional security for the parent and a model for

how to support the child. Although this study design was not experimental, this finding is also

consistent with previous research showing that families with higher risk levels benefit most from

early intervention programs (Bradley, Burchinal, & Casey, 2001; Robinson & Emde, 2004).

However, although program caregivers with higher levels of education (bachelor’s degree or

higher) tended to have less positive relationships with Early Head Start parents, we found that
when these more educated caregivers did establish positive relationships with parents, the quality
of the relationships was significantly associated with observed positive parenting behaviors. This

association between relationship quality and parenting outcome was significantly weaker for

caregivers with lower education levels. One possible conclusion from this pattern of results is

that building positive relationships with parents might be an important and necessary step for

higher educated staff to help families achieve more favorable program outcomes. Overall,

our findings suggest that program caregivers with varying levels of experience or education do

productively engage families and do promote positive program outcomes for children and families,

perhaps in distinctive ways. Also, individualized approaches to in-service training and other

EARLY HEAD START RELATIONSHIPS 511

program supports may be needed for program caregivers with different backgrounds, so that

each one is able to engage families, develop positive relationships, and use those relationships

to support positive changes in children and parents.

As with many intensive observational field studies of early childhood programs with high-

risk clients, limitations stemmed from a smaller sample size and the attrition of research parti-

cipants over time. The use of larger samples and additional strategies to retain study participants

will be beneficial in future research examining program relationships with Early Head Start

families. Finally, although multilevel modeling analyses were conducted to address the issue

of nested data, future research should strive to examine interpersonal relationships within more

homogeneous program contexts or in samples of sufficient size to tease out all of the patterns of

nested groups.

This study breaks new ground with its focus on the assessment and description of Early Head

Start caregiver relationships with both children and parents over time, using multiple measures

and methods to assess relationships and program outcomes. The findings challenge researchers

and practitioners to consider variations in program relationships and the fact that these relation-

ships can be an important aspect of the intervention. The results reinforce the findings in

previous research that it may be challenging to develop supportive relationships with parents

who have lower levels of education. However, positive and supportive relationships with

program caregivers may support more positive outcomes for those who are at risk for negative

parenting or less optimal child development outcomes. Likewise, these results suggest that it

may be more challenging for caregivers to develop relationships with boys and toddlers than

with girls and infants, so these issues may also be important to consider as staff are guided to

build secure, positive relationships with children.

The study of relationships in early intervention programs is a complex matter. The relational

experiences that young children, parents, and professionals have when they come together in

a program like Early Head Start are rich and variable. Relationship constructs such as attachment

security have been tremendously helpful in understanding and supporting early development.

However, researchers will certainly need more differentiated relationship constructs and ways

of assessing them in the future study and improvement of relationship-focused early intervention

programs like Early Head Start.

ACKNOWLEDGMENTS

This research was supported by a Head Start-University Partnership grant (#90YD0111=03)
from the U.S. Department of Health and Human Services, Office of Planning, Research, and

Evaluation. The authors are especially grateful to the children, parents, and staff who

participated from the Early Head Start partner programs in Lafayette, Indiana (Bauer Family

Resources), Kokomo, Indiana (Bona Vista Programs), and Marion, Indiana (Carey Services).

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Running head: HOW TO EVALUATE AN EARLY HEAD START PROGRAM IN the UNITED STATES 1

HOW TO EVALUATE AN EARLY HEAD START PROGRAM IN the UNITED STATES 6

How to Evaluate an Early Head Start Program in the United States

Taliqua S. Medley

North Carolina Central University

February 5, 2018

Dr. Daniel Pryce

Introduction/Literature Review

Program evaluation is a systematic method that allows policy makers, planners, program managers, or program clientele to evaluate and assess programs about their effectiveness (Rossi, Lipsey, & Freeman, 2013). Evaluating programs bring out both the strengths and weaknesses, but also identifies a visual of the plans implemented. The purpose of program evaluation is to distinguish social programs from ineffective ones and launch new programs or revise existing programs to achieve better results. For program evaluation to be done properly, policymakers must obtain answers to certain questions. Some of these questions are as followed: what are the nature and scope of the problem? Who is the appropriate target? Is the program cost efficient?

According to Rossi, Lipsey, & Freeman (2013), all evaluations must be tailored to specific circumstances so that the information gathered is credible and useful to answer necessary questions. There are three issues that raise concern about evaluations. First, the questions the evaluation is to answer. More specifically, who the primary target is, is the program making an impact as it was designed to do, and is the program cost efficient. Next, the methods used to answer these questions. It is important for all evaluators to be able to obtain credible and timely information about the different aspects of the program. Lastly, the evaluator-stakeholder relationship.

Evaluators may serve as a consultant while the stakeholder is responsible for planning and using the evaluation. It is possible that the evaluator may seek additionally support from stakeholders. Within the relationship both parties should understand what information to receive at what times, the nature of the plan, and how the findings should be spread beyond the sponsor. For an evaluation plan to be effective there are three principles features to consider. The purpose of the evaluation, the structure and circumstances, and finally, the resources available (Rossi, Lipsey, & Freeman, 2013).

The purpose of evaluation is broken down into four segments. Formative evaluation relates more so to furnishing existing programs (Rossi, Lipsey, & Freeman, 2013). In other words, make better of an existing program. For accountability purposes, taxpayers want to know that their money is going to be used carefully, and strategically. If program managers use resources that produce benefits it is called summative evaluation. Many evaluations are based on the contribution to knowledge. Because of this they are implemented using feasible methods. Finally, hidden agendas, often the purpose of evaluations has little to do with gathering information about the progress of the program.

All programs are different. Even if they have a common goal, not one of them have the same exact structure. For evaluators, there are three important categories: the stage, administrative and political context, and organization structure of the program (Rossi, Lipsey, & Freeman, 2013). The stage of program development can alter at various times. Growing up I always heard the saying desperate times case for desperate measures. Relating this to program evaluation, when evaluators see that a specific program no longer has the same effect they begin strategizing and coming up with new ideas.

It is important to understand that evaluators do not establish their own goals (Rossi, Lipsey, & Freeman, 2013). The evaluator works with sponsors, program management along with other stakeholders to develop a program. Of course, with there being different types of people there will be different opinions as well. The evaluator will take input from all stakeholders and incorporate all concerns. Additionally, if all parties are not in an agreement about the purpose and what steps are needed for an effective program that will cause conflict.

According to Rossi, Lipsey, & Freeman (2013), if evaluators do not know the purpose of a program they cannot effectively evaluate the program. The program theory is the “plan of operation, the logic that connects its activities to the outcomes, and the rationale for why it does what it does” (Rossi, Lipsey, & Freeman, 2013, pg. 44). It is very imperative that evaluators understand the organizational structure of the program as well. The larger the program is, the more complex the structure will be. It is easier for evaluators to evaluate concrete activates, such as meals to the homeless.

For resource purposes, evaluators must be sure that they have the required resources. Evaluation plans must accommodate that there will be limitations on the amount of resources available. Program evaluation requires critical resources such as: funding and the amount of time that is allotted to complete work. Evaluators must be expertise in understanding that there must be a balance between what is most desired rather than what is more feasible.

With every program there are certain individuals with roles. Program managers, policy makers, program staff, sponsors, target participants are all individuals who contribute to the implementing a program. According to Rossi, Lipsey, & Freeman (2013), there are three types of evaluation; independent evaluation which assumes the evaluator takes primary responsibility, participatory evaluation which assumes the program requires a team of people, and lastly, empowerment evaluation which is a participatory evaluation in which the evaluators roles include facilitation directors to stakeholders. It is important for all evaluators to ensure that the relationship that they have with other stakeholders is a good one. Especially if they are individuals with the same interest, or who just want to help.

A program evaluation is gathering information to answer questions about how a program is doing or how it can be improved. An important tactic in doing so, is deciding what questions best answer those questions. There are five commonly recognized issues surrounding that evaluation questions fall into: needs assessment, assessment of program theory, assessment of program process, impact assessment, and efficiency assessment.

Needs of assessment is the implication for intervention of a program. Assessment of the program focuses on how the program is designed. Assessment of program process is focuses on the effectiveness of the program. The impact assessment is an overview of how the program works. Lastly, efficiency assessment compares the cost of the program to how much effectiveness there is.

For this paper, we will assume that the Head Start program being evaluated is designed to provide services to low-income women with infant children and toddlers up to three years of age. It is vital to understand that Early Head Start is a comprehensive program that focuses on enhancing children’s development while providing educational opportunities. Despite programs having many purposes, most aim to reduce gaps in school readiness between low-income and more advanced children (Raikes, Brooks-Gunn, & Love, 2013). To make things a little clearer, it is most common for low-income children to enter school at a standard deviation lower than most children in domains such as vocabulary and cognition (Raikes, Brooks-Gunn, & Love, 2013).

The development of Early Head Start “suggests that interventions are likely to change the slope of developmental trajectories and that differential experiences of children during various periods may influence different aspects of child well-being” (Raikes, Brooks-Gunn, & Love, 2013, pg. 4). According to Bachman & Schutt (2015), individuals who have interest in the program are called stakeholders. These individuals provide information about the process, outputs, and any outcomes available. Inputs are referred to as resource managers and staff, the program process entails different activities and services that the program provides, outputs are what is being delivered, and the outcome is the impact the program.

Program Stakeholders

The Head Start program stakeholders are parents, teachers, community members, program managers, staff caregivers and other individuals interested in the effectiveness of the program. The individuals will provide information about how the program is progressing and the necessary steps that need to be taken to improve the program. To engage these stakeholders, the parents are going to be responsible for the staff is going to be responsible for conducting an orientation to give an overview of what is expected from all stakeholders and the goals of the program, reflective meetings about the children and their process, and regularly staff meetings. Parents are responsible for providing updated information about the child’s progress.

Program Inputs

Program director, lead teacher, breakfast/snack

Program Outputs

According to Elicker, Wen, Kwon, & Sprague (2013), similar to this very program, the importance is to build positive relationships participating caregivers and families to support positive change.

Timley, kids may age out.

References

Dickstein, S., Seifer, R., Eguia, M., Kuersten-hogan, R., & Magee, K. D. (2002). Early head start MAP: Manualized assessment of progress. Infant Mental Health Journal, 23(1/2), 231-249.

Elicker, J., Wen, X., Kwon, K., & Sprague, J. B. (2013). Early head start relationships: association with program outcomes. Early Education & Development, 24(4), 491-516.

Gettinger, M., & Stoiber, K. (2007). Applying a response-to-intervention model for early literacy development in low-income children. Topis In Early Childhood Special Education, 27(4), 198-213.

Raikes, H. H., Brooks-Gunn, J., & Love, J. M. (2013). I. Background literature review pertaining to the early head start study. Monographs Of The Society For Research In Child Development, 78(1), 1-19.

Rossi, P. H., Lipsey, M., & Freeman, H. E. (2004). Evaluation: A Systematic Approach (7 th ed.). Thousand Oaks, CA: Sage.

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