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An Empirical Study of Coexisting Relationships
Between Area-Specific Support and Early Childhood Development
Jianjun Wang
Department of Advanced Educational Studies, California State University, Bakersfield
9001 Stockdale Highway, Bakersfield, CA 93311, Phone: 661-654-3048, Fax: 661-654-2016,
jwang@csub.edu
Jamie Henderson
Executive Director, Kern County Children and Families Commission, 2724 L Street
Bakersfield, CA 93301
Judith Harniman
Assistant Director, Kern County Children and Families Commission, 2724 L Street
Bakersfield, CA 93301
Authors’ Notes
The authors wish to thank the Institutional Review Board of California State University,
Bakersfield for approving the human research protocol for this investigation. Appreciation is
also extended to the First 5 Kern Commission and its Technical Advisory Committee. The
research team received ongoing support from Theresa Martinez and Heather Schreiner.
Nonetheless, opinions expressed here are those of the authors, and do not necessarily represent
positions of California State University, Bakersfield (CSUB) or Kern County Children and
Families Commission (First 5 Kern). Inquiries should be directed to the corresponding author at
jwang@csub.edu.
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Abstract
Early childhood development is inseparable from healthcare, parental education, and
childcare services. Empirical data are gathered in this study from 131 children at age 3 to assess
coexisting effects from those area-specific services at 21 preschool communities across Kern
County, California. While muscle and bone growth occurs on scales of height and weight to
support improvement of motor skills, more dramatic development has been found across
communication, problem solving, and personal-social skills within the broad context of
environmental interactions that are otherwise not detectable from an isolated investigation of a
single service. To examine the well-rounded early childhood development at a county as large as
the state of New Jersey, a comprehensive Context, Input, Process, and Product (CIPP) model is
employed to identify pertinent variables from the current research literature and reconfirm the
relationship through empirical data analyses. The result suggests additional needs of
incorporating culture-dependent variables for future investigation.
Keywords: Coexisting Effect, Early Childhood Support, Service Integration, First 5 Kern
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An Empirical Study of Coexisting Relationships
Between Area-Specific Support and Early Childhood Development
Long before implementation of federal legislations, such as No Child Left Behind Act of
2001, on child education, California has led the nation in providing subsidized child care and
early childhood development for working parents (Arbegast, 2010). The first formal child care
centers, referred to as day nurseries, were founded in California in 1913 (see National Research
Council and Institute of Medicine, 1995). During World War II, the state government
strengthened its social services by sponsoring the State Child Care Center program (Karoly,
Reardon, & Cho, 2007). Two additional programs, California State Preschool Program and Aid
to Families with Dependent Children Program, were subsequently launched in the cold war era
with a clear focus on supporting children from disadvantaged homes (Reese, 1996). After the
cold war end, Californians further incorporated broad-based scientific research on brain
development to justify needs of state investment in early childhood services (Huttenlocher &
Dabholkar, 1997; McLloyd & Wilson, 1991; Nash, 1997). As a result of the long-lasting public
campaign, California Children and Families Act of 1998, also known as Proposition 10, was
supported by the state voters to fund services for children ages 0-5 with an additional 50 centsper-pack sales tax on cigarettes and other similar tobacco products.
Bodenhorn and Kelch (2001) recollected, “When California voters passed the Proposition
10 ballot initiative in 1998, they set in motion an unprecedented experiment to reshape how
California communities address the needs of very young children and their families” (p. 151).
With support from the tax revenue, Proposition 10 stipulated creation of First 5 Commissions to
lead the service delivery at both state and county levels. Accordingly, Kern County Children and
Families Commission (First 5 Kern) was established in 1998 to fund services in Kern County.
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While 20% of the tax revenue is retained by the state commission for state initiatives, the
remaining 80% are distributed at the county level according to the local birth rate (First 5
California, 2012). Kern County represents an exemplary case for having the highest birth rate
across California over the past decade (Wang, 2012). Since its inception, “First 5 [Kern] has
allocated more than $100 million to 450 programs sponsored by 240 different organizations
throughout Kern County” (Bedell, 2010, p. 1).
By making the county commissions a creative partner, not just a subordinate organization
of the state commission, Proposition 10 has strengthened the local control and accountability on
the revenue spending, and thus, promoted service access for the youngest children and their
families across the state. To track the public accountability, the state commission identified
specific focus areas through strategic planning. It was stipulated that “While counties design
their programs to fit their specific local needs, they must provide services in each of the
following four focus areas: Family Functioning, Child Development, Child Health, [and]
Systems of Care” (First 5 California, 2010a, p. 15). A purpose of this investigation is to examine
effectiveness of the area-specific support for early childhood development. Because the early
years of a child’s life form a foundation for later growth, the system of care across these focus
areas is likely to reduce the needs of extra funding for remedial education and welfare programs
in the future.
Nonetheless, the recent state budget crisis has deeply eroded foundation of the public
service for the local population. In March 2011, the state legislature passed Assembly Bill 99
(AB 99) with an attempt to take $11.7 million from First 5 Kern. This bill was part of the
Assembly’s response to a fiscal emergency declared by Governor Brown on January 20, 2011.
Prior to this proposed cut, Bodenhorn and Kelch (2001) admitted, “Although the resources of
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Proposition 10 represent a significant commitment to the early childhood years, they are
insufficient to fill all of the existing service gaps” (p. 156). The threat from AB 99 has made it
more imperative to examine the impact of First 5 Kern funding. In support of this timely
investigation, empirical data have been gathered from 21 preschool communities across Kern
County to analyze relationships between indicators of the area-specific service and early
childhood development in Fiscal Year 2010-2011.
Research Questions
The Carnegie Corporation’s (1994) Task Force on Meeting the Needs of Young Children
found that brain development during the first 5 years of life has been much more vulnerable to
environmental influence than was suspected. Since each child is born with intrinsic dispositions
that shape the individual experiences on multiple fronts, researchers suggested modeling of child
development as a latent construct with manifest indicators (Bandstra, Vogel, Morrow, Xue, &
Anthony, 2004). In addition, latent factors can be derived from multiple service areas to describe
the coexisting contributions to child growth (Denham, Blair, & Demulder, 2003). Thus, research
questions that guide this investigation are:
1. What indicators are pertinent to identification of child growth and its related services
according to the current literature?
2. What are the empirical relationships between indicators of the area-specific service and
early childhood development?
3. Does the statistical model fit the First 5 Kern database for this investigation?
While Questions 2 and 3 hinge on quantitative data analyses, answers to Question 1 depend on
establishment of a theoretical framework to articulate empirical indicators across multiple
service areas.
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Literature Review
California counties received numerous state and federal grants in the past, but local
communities have never had such a large, area-specific funding on an ongoing basis (Cousineau,
Stevens, & Pickering, 2007). As part of the funding requirement, “The Children and Families
Act of 1998 [i.e., Proposition 10] mandates the collection of data for the purpose of
demonstrating results” (First 5 Kern, 2011, p. 16). In March 2010, the state commission issued
“Guidelines for Implementing the California Children and Families Act” to reaffirm “the support
of local decision-making and the development of integrated strategies that are determined to be
most appropriate for each county” (First 5 California, 2010b, p. 6). In response, First 5 Kern has
developed a strategic plan to align the state focus areas with local priorities (Table 1).
_____________________
Insert Table 1 around here
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Local creativity was emphasized to address shortfalls of the government funding for child
care and development. It was stated in AB 99 that
California is presently experiencing a severe fiscal crisis, which has resulted in funding
shortfalls for many services at the state and local levels. Health and human services
programs that serve children are among the most seriously affected by this lack of
funding. (p. 1)
Thus, a business as usual approach no longer works, and local innovations are needed to enhance
effectiveness of the public spending.
Without a literature-based framework to streamline the knowledge accumulation, local
explorations often rely on repeated discoveries of similar solutions through trial-and-error
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methods. To avoid the disorganized inquiry, John Tukey (1980) advocated confirmatory
investigations through statistical modeling. He noted that “Ideas come from previous
exploration more often than from lightning strokes. Important questions can demand the most
careful planning for confirmatory analysis” (p. 23). To facilitate new knowledge acquisition,
data analyses in this study are guided by the research literature to model empirical results across
different areas of early childhood service.
The Context, Input, Process, and Product (CIPP) Model
Over the first decade of the 21st century, First 5 Kern has evolved from a fledgling
organization to an agency with strong accountability. According to the 2010 census findings,
Kern County’s population has increased 27% over the past decade, making it the fastest growing
county in California. Nearly 60% of the local residents live outside of the Bakersfield city
boundary, and local communities of various sizes spread over a valley land as large as the state
of New Jersey. Due to the important regional services, First 5 Kern has been recognized by the
state commission for its leadership in engaging isolated communities, including those hosting
migrant farm worker families (First 5 California, 2008). As tobacco consumption decreases, the
state funding inevitably declines. Thus, accountability is particularly critical to address the
extensive service demands with the shrinking resources.
While it takes a community to set a nurturing environment, parents still hold the
responsibility to care for their children (Tomlin, 2007). “Although a consensus exists about the
significant role that parents play in a child’s development, there exists neither a singular ‘one
size fits all’ approach to parent education that has been promulgated statewide, nor any major
local initiatives” (Zepeda & Morales, 2001, p. 5). Since no program is equally effective under
any circumstances, the state statutes “emphasize local decision-making, to provide for greater
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local flexibility in designing delivery systems, and to eliminate duplicative administrative
systems” (FindLaw, 2011, p. 1). To support the systematic approach, a context, input, process,
and product (CIPP) model is employed to guide this investigation. As Sloane (2008) suggested,
“We change the basic research question from what works to what works for whom and in what
contexts” (p. 43).
Since new local context evolves from the previous product outcomes, the CIPP paradigm
provides a sustainable platform to support the ongoing progress. In addition, the context phase
readily incorporates the spirit of local control promoted by the state legislation. Since its
adoption in the 1960s, the CIPP model supported evaluation of numerous projects to address
needs of various stakeholders (Stufflebeam, 1983; Wang, 2011). Meanwhile, the model itself
matured through a process of developing national evaluation standards over the past four decades
(Program Evaluation Standards, 2010; Yarbrough, Shulha, Hopson, & Caruthers, 2010). As a
proven example, White (1981) has acknowledged that the Context, Input, Process, and Product
(CIPP) paradigm represents “the most comprehensive evaluation model” in the field (p. 217).
Contextual Support for Service Access
From the contextual perspective, concerted efforts have been made by First 5 Kern to
improve service access for local children, including those of rural communities. As part of the
effort on local capacity building, First 5 Kern funded mobile services, such as Kern County
Children’s Dental Health Network and Children’s Mobile Immunization Program, to serve
children and families in hard-to-reach communities (Wang, 2012). In addition, a support
network has been established to assist children of Kern County on health insurance application.
In the 2011-12 fiscal year, “99% of Kern County residents have available application assistance
within ten miles of their community” (Wang, 2012, p. 14).
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Considering parental education as an important attribute, Kern County is ranked among
the lowest regions across the United States (Brookings Institution, 2010). At the county seat,
Zumbrun (2008) concurred that Bakersfield was ranked as one of the least educated metropolitan
areas across the nation. Thus, the application assistance paved the way for healthcare access
within the local communities. In Fiscal Year 2010-2011, First 5 Kern funded 21 preschool
programs across Kern County to enhance parent education and early childhood education. The
site choice is grounded on a balanced consideration of transportation network and population
distribution. As a result, “With First 5 Kern funding, greater Bakersfield and Kern County’s
rural and mountain communities have local access to services that would otherwise be
unavailable” (Henderson, 2011, p. 1).
Input Characteristics
Neural scientists indicated that brain development is adaptive to both deleterious and
beneficial experiences that impact early childhood growth (Nelson, 2000; Shonkoff & Phillips,
2000). Hence, supportive and preventive measures are incorporated in the input phase to assist
early child development. The earliest supports start from prenatal care. Low birth weight has
been linked to prenatal care in the research literature (Rosenberg, 2004). As was cautioned by
Lu, Bragonier, Silver, and Bemis-Hey (2000), “Nearly two thirds of neonatal and infant deaths in
the United States and in California occur in the low birth weight population” (p. 3).
Bull (2003) added that “Smoking in pregnancy is a serious health risk to mother and baby
that is associated with premature birth, low birth weight and respiratory disorders” (p. 661).
Similar to prenatal care, “Quitting smoking before pregnancy may significantly reduce the risk of
low birth weight in the infant” (Lu et al., 2000, p. 9). In this study, indicators of prenatal care
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and smoking prevention are incorporated to assess effectiveness of First 5 Kern services at the
input phase.
Researchers found that children were at greater risk for growing up poor with inadequate
parent education (Duncan, Yeung, & Brooks-Gunn, & Smith, 1998). More specifically, “failure
to learn to read adequately is much more likely among poor children, among Non-white children,
and among nonnative speakers of English” (Regalado, Goldenberg, & Appel, 2001, p. 4). Since
more than 49.2% of the Kern County population has Hispanic or Latino origin, family income
and parental education are the pertinent indicators of the input conditions prior to the service
delivery.
In contrast to the threats encountered by poor children, children of affluent families could
be "pressured but neglected" by their parents (Ansary & Luthar, 2009; Luthar & Latendresse,
2005). Although modern technology has replaced human labor on numerous fronts, parenting
effort remains irreplaceable. “New research from Peabody College [Vanderbilt University] and
the University of Virginia finds that infants learn little to nothing from popular educational
videos and learn the most from face-to-face interactions with their parents and other familiar
figures” (Troseth, 2011, p. 9). Unfortunately, shirking of parental duty has gained popularity in
affluent families in recent year with more people admiring a “dual income, no kids” (DINK)
lifestyle (United Nations Children’s Fund, 2007). The lack of parental commitment could create
negligence in the home environment, causing an irrecoverable loss of learning opportunity for
children (Lareau, 2002).
Facing the increasing demand on early childhood services, First 5 Kern has developed a
vision to help all Kern County children enter school healthy and ready to learn. With its areaspecific funding, school readiness is prepared through childcare, health care, and parental
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support, regardless of the individual differences in socioeconomic status. To reflect the holistic
development of children on multiple fronts, First 5 Kern funded well-rounded services that are
community-based, family-focused, and culturally appropriate for the youngest population of
Kern County to grow physically, mentally, emotionally, and cognitively in a healthy
environment.
Features of the Service Process
Through the First 5 Kern funding, the health care service covers enrollment, access,
retention, and utilization of health insurance (First 5 Kern, 2011). Regular health screenings are
included in the insurance coverage, and this practice has been found to reduce emergency room
visits (Lasker, 1997). In addition, Schneiderman, McDaniel, Xie, and Clark (2010) identified
“wait too long to see a doctor” as a most difficult access barrier. Thus, timely health checkups
turn into a cost-saving indicator in the health care domain.
Another indicator of health service is dental care. Shobo (2002) pointed out, “although
dental disease is preventable, dental decay is still the most common and costly oral health
problem among children” (p. 1). More importantly, dental checkups do not preclude children at
early ages. As Sears (1988) indicated,
Babies should receive their first dental checkup at six months, when their baby teeth start
to erupt, … Early checkups enable dentists to evaluate a child's risk of dental disease
based on hereditary, medical, and environmental factors; to begin preventive measures
such as correct brushing techniques; and to prevent cavities caused by bottle feeding. (p.
32)
Similar to the needs of early health checkups, it is important to promote early childhood
development. Armbruster, Lehr, and Osborn (2006) reported that “Learning to read and write
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can start at home, long before children go to school” (p. 1). To address the need of preschooling, First 5 Kern sponsored nursery education for children on a regular basis. Hannon and
James (1990) recollected that “Nursery education has traditionally been used in developing
specific pre-reading skills” (p. 259). Naturalistic studies also confirmed the linkage between
child literacy tuition and parenting skill development (Heath, 1983; Taylor & Dorsey-Gaines,
1988).
In summary, it has been required that “the state and county commissions shall use
outcome-based accountability to determine future expenditures” (Proposition 10 Statutes, p. 1).
The CIPP model demonstrated the mechanism of justifying improvement in the product phase
beyond baseline indicators. While service indicators have been identified from the literature
review section, the indicator choice should be extended beyond the context, input, and process
perspectives. Child growth outcomes need to be examined to justify the population
accountability under the CIPP paradigm.
Method
Weiss (2010) noted that California has established “a comprehensive, integrated system
of early childhood development services from the prenatal period to age five” (p. 243). To
assess the integrated impact at the product phase, this section recaps indicator identification
pertinent to First 5 Kern services, and incorporates outcome measures of early childhood
development to examine effectiveness of the co-existing area-specific supports in the local
context.
Local Service Indicators
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To meet Proposition 10 requirements, effort has been made by First 5 county
commissions to track explanatory variables in a Core Data Element (CDE) database. According
to Harder+Company Community Research (2004),
CDEs are an important part of data collection for First 5. The CDEs are questions that
form the basis of data collection for the Commission ... The CDEs help the Commission
understand the characteristics of clients that are served and also highlight areas of unmet
needs in the County. (p. 19)
Under the auspices of Kern County Children and Families Commission, multiple
indicators have been incorporated from the CDE data to support examination of the area-specific
services. More specifically, children’s healthcare is identified by prompt (1) health checkups
and (2) dental care services. Early childcare is reflected by issues of (1) late prenatal care and
(2) smoke exposure. Support for those indicators of healthcare and childcare have been
examined in the section of Literature Review (e.g., Bull, 2003; Lasker, 1997; Lu et al., 2000;
Rosenberg, 2004; Schneiderman et al., 2010; Sears, 1988; Shobo, 2002).
The literature also endorsed parenting effort on strengthening reading literacy in early
childhood development (Bartholomew, & Gustafsson, 1997; Furman, 1986; Wolff, 2002). The
effort can be directly indicated by the time parents spent on reading books to their children
(Armbruster, Lehr, & Osborn, 2006). In addition, it is desired to have parental support for
nursery education at a center-based location (Hannon & James, 1990). As Hewes (1997)
recalled,
Typical cooperative nursery schools in past years have required car-pooling mothers to
work one morning a week, and the doors are locked by lunch time. Many are adapting to
the changed environment by permitting “buy out” time or flexibility in participation,
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providing both half-day nursery school and extended hours, and making other
modifications to fit today’s lifestyles. (p. 25)
Accordingly, the CDE instrument incorporated indicators of support from both aspects of home
reading and nursery education (see Figure 1).
______________________
Insert Figure 1 around here
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With a computer software package of Linear Structure Relation (LISREL) that can handle
indicators on dichotomous and/or ordinal scales (see Jöreskog, 1990), the factor of parenting
effort is indicated by (1) parent support for regular attendance of nursery schooling by the
children and (2) number of reading hours parents had for children in a week.
In examining the relationship between family resources and childcare services,
researchers found support from Maslow's theory on the hierarchy of human needs (Nicholas,
2006; Norwood, 2009). While family income is essential to supporting the basic nutrition and
body needs (Duncan, Yeung, Brooks-Gunn, & Smith, 1998; Gray, Byrd, & Cossman, 2007),
child mental development is strongly link to parental education at the top of Maslow’s hierarchy
(see Beatty, 2005; Heath, 1983; Taylor & Dorsey-Gaines, 1988). To cover these hierarchical
needs, family resources are described by indicators of annual family income and parental
education. The use of indicators has become a general practice to study latent variables
(Loehlin, 1992). In fact, “The representation of latent variables based on their relation to
observed indicator variables is one of the defining characteristics of SEM [Structural Equation
Modeling]” (Garson, 2005, p. 3).
ASQ Measures
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In this study, individual performance scores were gathered from an Ages & Stages
Questionnaire (ASQ) to assess well-rounded outcomes of child growth. According to Crossley
(2012), “Though many screening tools are in use today, few have been as rigorously researched
as ASQ” (¶. 4). In particular, its current version (i.e., ASQ-3) has gone through field testing of
15,138 children from all 50 states and several U.S. territories that mirror the U.S. population in
terms of race, ethnicity, and socio-economic groups (Assuring Better Child Health &
Development, 2012). As Kerstjens et al. (2009) reported,
Amongst the parent-completed questionnaires for young children, the Ages and Stages
Questionnaire (ASQ) is currently the most widely used. … It has been translated into
Spanish, Korean, Chinese, French, Danish and Norwegian, and several other local
translations exist. (p. 444)
In addition, “The original ASQ [in English] has been proven to be reliable and costeffective with excellent psychometric properties” (Kerstjens et al., 2009, p. 444). In Branson’s
(2009) study of the ASQ feasibility, “The majority of childcare providers (89%) demonstrated
high agreement between their developmental impression of a child and ASQ results” (p. i).
Nicol (2008) concurred that the ASQ measurement “has been shown to be reliable and valid” (p.
20). The instrument is also readable for most parents because “ASQ questions are written at the
fourth to sixth grade reading level” (Branson, 2009, p. 43).
With approval from the Institutional Review Board (IRB) of California State University,
Bakersfield (CSUB), the ASQ scores were gathered for this investigation during the first two
quarters of Fiscal Year 2010-2011. The time choice coincided with the outbreak of California
budget crisis that led to the passage of Assembly Bill 99. A total of 131 children were assessed
across 21 preschool programs throughout Kern County.
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As a screening instrument, “[ASQ] Scores beneath the cutoff points indicate a need for
further assessment” (How ASQ Works, 2011). Thus, late assessments of the same type only
occurred to those slow children at ages 4 or 5. Early results at ages 1 or 2 seemed too premature
to examine school readiness. To strike for balance, this study focuses on the ASQ-3 findings at
age 3. The age selection is concurred by rationale of Proposition 10:
It has been determined that a child's first three years are the most critical in brain
development, yet these crucial years have inadvertently been neglected. Experiences that
fill the child's first three years have a direct and substantial impact not only on brain
development but on subsequent intellectual, social, emotional, and physical growth. (sec.
2c)
Similar to the CDE data collection, utilization of the ASQ measure has been a common practice
of First 5 county commissions across California to assess early childhood development
(Fitzgerald, Sormano, & Ramirez, 2010).
In summary, the ASQ choice is supported by the current research literature in early
childhood services and the past practices of First 5 commissions across other counties of
California. Following the ASQ-3 administration guideline, indicators of child growth are based
on ASQ scores in five aspects – communication, gross motor, fine motor, problem solving, and
personal-social skills. The use of multiple indicators is designed to better represent the latent
variable of child growth from multiple aspects. In addition, it facilitates assessment of potential
measurement errors in the statistical computing (Loehlin, 1992; Sharma, 1996). As Schumacker
and Lomax (1996) observed, “Today, it is commonly accepted that multiple observed variables
are preferred over a single variable in defining a latent variable” (p. 55).
Statistical Computing
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Structural equation model (SEM) is a statistical technique that models relationships
among latent variables through empirical data analyses. It embraces advantages of factor
analysis and path analysis, and includes multiple regressions as a special case (Bollen, 1989;
Kline, 2010). More importantly, “Structural equation models (SEMs) also called simultaneous
equation models” (Fox, 2002, p. 1). The simultaneous nature fits the coexisting contributions of
First 5 Kern services in multiple fronts, including childcare, health care, family resources, and
parenting efforts. Although family resources, such as annual income and levels of parent
education, are not directly modifiable through the First 5 Kern funding, these attributes are
embedded in the context of family functioning to support the area-specific funding. Therefore,
the SEM method endorses a holistic examination of early child development in the investigation.
The SEM analysis is supported the LISREL software (Jöreskog, Sörbom, Toit, & Toit,
2000). Relationships between child ASQ scores and area-specific factors are depicted in Figure
2. In justifying the accountability on state funding, path coefficients () are estimated to assess
what works in the local context. Factor loadings () have been computed to delineate features of
latent variables in terms of their manifest indicators.
______________________
Insert Figure 2 around here
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To assess whether the statistical findings have been supported by the First 5 Kern
database, LISREL is employed to compute an overall Goodness-of-fit index (GFI) that describes
the percent of observed covariances explained by the covariances implied by the model (Kline,
2010). In addition, the internal model fitting is represented by the Comparative Fit Index (CFI).
A low CFI value is anticipated if the average correlation between the manifest indicators is not
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high (Kenny, 2010). The Root Mean Square Error of Approximation (RMSEA) index is used to
examine the model fit against an external benchmark – good models are considered to have a
RMSEA of .05 or less (Hu & Bentler, 1999). In this study, the CFI, RMSEA, and GFI indices
are evaluated to justify the model confirmation.
Results
Figure 2 includes parameters from the measurement model and structural relation parts.
Factor loadings () are presented in Table 2 to model latent variable features using manifest
indicators. In addition, the structural relations are described by path coefficients () to reflect
contributions of the latent variables toward outcomes of early childhood development. Those
two parts are jointly presented in Table 2 to triangulate interpretations of the and  values in
the Discussion section.
_____________________
Insert Table 2 around here
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Meanwhile, statistical computing has been conducted to produce the model fitting
indices. In particular, goodness of fit index (GFI) in Table 3 indicates overlap of covariances
from fitting the observed data into the SEM model in Figure 2. Comparative fit index (CFI) is
used to correct “underestimation of fit often noted in small samples” (Bentler, 1990, p. 238).
The index of root mean square errors of approximation (RMSEA) is provided to assess the
average of residuals not accounted for by the model. The high GFI and CFI indices and small
RMSEA values reconfirm the model fitting results for this investigation.
_____________________
Insert Table 3 around here
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Discussion
Ong (2006) pointed out, “When thinking about children’s readiness for school, one must
essentially consider the ‘whole child’ or all aspects of development” (p. 25). Recognition of the
coexisting effects is a unique feature of this investigation. It directly reflects concurrent services
of First 5 Kern on multiple fronts. “This distinction also recognizes that a single program,
agency or service system cannot take sole responsibility (or credit) for achieving a desired
condition of wellbeing for a whole population” (Gapstone Project Guide, 2008, p. 2).
First 5 Kern is a local commission that distributes Proposition 10 funding and oversees
the population accountability in Kern County. Friedman (2011) clarified that “OBA [Outcome
based Accountability] keeps population accountability separate from performance accountability.
Population accountability belongs to partnerships” (p. 4). Although area-specific supports are
not something new (Bodenhorn & Kelch, 2001), few researchers have examined concurrent
impact of multiple services in early childhood development. In part, this is because program
evaluations are often designed to address performance accountability within a funding area
(Moodie-Dyer, 2011). To fill out the void, this investigation includes an exploratory part to
articulate coexisting service outcomes across different funding areas.
In addition, guided by the tasks specified in the research question section, this study also
features a confirmatory component according to the CIPP model. The model is grounded in an
extensive literature base. Stufflebeam (1983) pointed out, “The CIPP approach is based on the
view that the most important purpose of evaluation is not to prove but to improve” (p. 118).
While accountability is important for state reporting, it is more important to examine empirical
findings from the local setting to sustain the service improvement. Therefore, the confirmatory
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inquiry focuses on interpretation of statistical findings to verify indicator identification from the
current literature.
Reconfirmation of Indicator Identifications
Under the CIPP paradigm, attributes of family resource have been incorporated in Figure
2 to support the indicator configuration in the product phase. Howes and Brown (2000)
synthesized a general approach in examining the family context, and concluded that “researchers
first accounted for family influences and then looked at the influences of child care beyond the
contributions of the parents’ education, income, and behavior” (p. 3). Whereas behavior
measures often involve various confounding variables (Carlo, Crockett, Randall, & Roesch,
2007), annual income and parental education are manifest indicators representing financial and
human resources in the family context.
Despite individual differences since birth, research literature indicates that most children
experience similar stages at approximately the same age (Case, Okamoto, & Griffin, 1996; Piek,
Baynam, & Barrett, 2005). Table 2 includes the child growth indicators in communication, gross
motor, fine motor, personal social, and problem solving domains. While development of the
gross and fine motor skills is related to a control of large and small muscles, communication,
personal social, and problem solving skills are more dependent on the environment. McManus
(2009) pointed out, “children's development evolves toward competence through on-going
transactions between themselves and their environments” (p. 17). Because of the inclusion of
additional outcome measures involving environmental interactions, impact on child development
can be compared in this study across those outcome indicators. The results showed higher factor
loadings () are derived from the communication, personal social, and problem solving
indicators (Table 2). Without considering the joint impact from environment, an isolated study
COEXISTING RELATIONSHIPS
21
of child growth could have been delimited to the gross motor and fine motor aspects, and thus,
failed to address major components of individual growth.
Hence, the ASQ outcome measures have supported an integrated approach of this
investigation to reveal stronger influences from the environment. While muscle growth is
visible, latent outcomes in the affective domain are intimately linked to the environmental
exposure (Christensen, Montanez, Corr, & Medinger, 2005). As Barker (2001) observed,
Any time from eight months onwards your baby will begin to realise he is a separate
person from you. He will find it exciting to be able to move away from you but scary
when you move away from him. (p. 1)
Because “Identity is a social construct” (Walshaw, 2007, p. 93), social services play an important
role in establishing a healthy environment to support early childhood development.
In alignment with the comprehensive child growth in multiple aspects, the parenting
effort factor is not confined within the home setting. Across the county, First 5 Kern sponsored a
total of 21 preschool programs to facilitate child growth in a center-based environment. Hence,
parents need to incorporate child learning opportunities at home and in the community. Besides
maintaining reading hours for children, they are expected to support nursery education at a
preschool site. A positive path coefficient (=.13) has been found from the parenting effort
factor on early childhood development when the effort is more or less balanced between weekly
reading (=.38) and preschool support (=.35).
While significant associations have been found between poverty and child learning
outcomes (Crooks, 1995), “new evidence shows low-income children in higher-quality settings
can begin to catch up to their peers” (Klein & Knitzer, 2006, p. 13). Thus, the center-based
support seems as important as the home-based reading effort. The statistical analysis in this
COEXISTING RELATIONSHIPS
22
aspect has confirmed the comparable factor loadings in identifying the parenting effort factor for
the benefit of early childhood development. Without the integrated investigation on parenting
effort, environmental indicators cannot be jointly disentangled between the aspects of home
reading and nursery education.
Likewise, factor loadings () are articulated with path coefficients () to portray
contributions from other service areas. For instance, the health care factor has a positive path
coefficient (=.89) because of its positive factor loadings from the health checkups (=.28) and
dental care (=.33). In comparison, the factor loading is slightly larger for the dental indicator.
The additional emphasis is well-justified because “There are far more people without dental
insurance than without medical insurance” (Platt & Cabezas, 2000, p. 4).
In addition, the childcare factor is reversely scaled by a negative factor loading on
prenatal care (=-.31) and a positive factor loading on smoke exposure (=.12). Thus, a path
coefficient of -.03 (i.e., =-.03) has been obtained to reflect the need of improving childcare in
the local context. Both indicators reconfirmed Kern County needs suggested by other studies.
For instance, Lucile Packard Foundation (2012) reported the rate of prenatal care for Kern
County at 76% while the state rate has reached 83%. Smoke cessation has been placed as a
priority of child protection, and Lu et al. (2000) urged that “We recommend that each county
Proposition 10 Commission consider allocating a portion of its Proposition 10 monies to
expanding local efforts on prenatal smoking cessation” (p. 29).
Part of the need for parental education is to create a healthy environment for child
growth. Thus, “From a developmental perspective, any encouragement to parents to pay more
attention to their children and their children’s responses is most likely a good thing” (Halfon,
Shulman, & Hochstein, 2001, p. 16). In comparison, mothers take care of more childrearing
COEXISTING RELATIONSHIPS
23
tasks, such as prenatal care and breast feeding. Regalado, Goldenberg, and Appel (2001)
discovered more influences on child development from maternal factors. Results from this
investigation support the importance of parent education with high factor loadings. Consistent
with the findings from research literature, mother’s education shows a higher factor loading
(=.84) than the one on father’s education (=.78) in this integrated model of child growth
(Figure 2).
Still, not all the indicators demonstrate a pattern of “the more the merrier”. One
counterexample is illustrated by the negative path coefficient (=-.23) from the family resource
factor. While traditionally underserved families need additional resources (Duncan, Yeung,
Brooks-Gunn, & Smith, 1998), the funding from First 5 Kern cannot address the issue of
affluenza. Koplewicz, Gurian, and Williams (2009) delineated,
The country music star Wynonna Judd amassed a fortune and squandered much of it,
throwing money at her children out of guilt for missing hockey practices and buying
more cars than she could ever drive. … Ms. Judd's remark epitomizes the no-win
situation in which many American families have found themselves—victims of the allconsuming affliction—a condition known as affluenza. (p. 1053)
Hence, First 5 Kern resources appear to be less needed by families of high socioeconomic status.
The greater the family resource, the less the need for subsidy. The opposite relationship has been
reflected by the negative path coefficient from the family resource factor.
Impact on Early Child Development
Research Question 2 addresses coexisting relationships between factors of the areaspecific service and early childhood development. To make a difference in the service outcomes,
it is important to recognize that some indicators are not adjustable and others can be altered
COEXISTING RELATIONSHIPS
24
through First 5 Kern support. For instance, family resources represent a contextual attribute
because First 5 Kern does not generate additional sources of family income. While poverty is
often linked to a minority status (Duncan, Yeung, Brooks-Gunn, & Smith, 1998), the service
cannot change ethnicity status. Nonetheless, “poverty and minority status pose significant
barriers to gaining access to both primary care and dental care” (Platt & Cabezas, 2000, p. 5). In
this study, the health care factor is indicated by timely health checkups and dental care, both
being covered by grant-sponsored insurance from First 5 Kern. Because of the insurance
coverage extended by Proposition 10, children in hard-to-reach communities have been granted
service access to health care. As a result, paramount relationship (=.89) has been found
between health care and child growth.
To reflect the joint effect on early childhood development, each path coefficient ()
should be interpreted in the context of concurrent area-specific services, which makes the
integrated model more realistic than an isolated model of a single aspect. For instance, when
prenatal care is considered in isolation, Halfon, Shulman, and Hochstein (2001) reported that
“the contribution a healthy pregnancy makes to optimal brain development might be comparable
to that of appropriate interaction between parents and children once they are born” (p. 3). With
inclusion of an additional smoke exposure indicator, the childcare factor has incorporated
prenatal conditions to jointly reflect early childhood protection. Because of the additional
influence channeled through the health care domain, the impact of childcare is not confined by
its direct relationship to child growth with a relatively small effect size (|=.03). Additional
contribution has been channeled through health care to generate the largest path coefficient
(=.89) across all service areas.
COEXISTING RELATIONSHIPS
25
It should be noted that the health care need is reversely linked to family resources.
Whereas the subsidy from Proposition 10 provides an important support for traditionally
underserved children, particularly when the local unemployment rate has reached 17.1% in
recent years (Rhoades, 2009), the state funding is less crucial for affluent families. Thus, a
negative path coefficient (=-.23) has been obtained to reflect the reduced impact for children
with more family resources.
An analysis of the coexisting effects is needed to enhance mutual supports among
different service domains. While the contribution of health care is built on coexistence of
impact from childcare, parenting effort, and family resource, early childhood development is
reciprocally linked to the quality health care as a foundation. Wright et al. (2001) pointed out:
Without appropriate content and quality of health care, many cognitive, speech, language,
and other developmental problems and issues will go unidentified, parents will not
receive important counseling to help them stimulate their children’s learning capacities,
and children’s school readiness will be in jeopardy. (p. 1)
The integrated services sponsored by First 5 Kern are grounded on an assumption that the whole
could be greater than the sum of its parts. While programs in the healthcare domain incorporate
education components to disseminate current knowledge on childcare and protection, education
programs reciprocally support healthcare agencies in expanding the service access, including
working with parents on information sharing and insurance policy application (Wang, 2012).
The joint effort addresses the fourth priority of First 5 Kern, i.e., establish a well-integrated
system of services for children and families. The results from this investigation extend
additional support for the inter-agency collaborations across those area-specific services that are
essential for early childhood development.
COEXISTING RELATIONSHIPS
26
Model Fitting Indices
Schumacker and Lomax (2004) further pointed out, “Model fit determines the degree to
which the sample variance-covariance data fit the structural equation model” (p. 91). To
evaluate the empirical support of the statistical model in Figure 2, multiple model fitting indices
are examined in this section to triangulate the results.
Overall, the model fit indices are classified into three major categories of model fit, model
comparison, and model parsimony fit indices (Hooper, Coughlan, & Mullen, 2008; Schumacker,
& Lomax, 2004). On the model fit part, the goodness-of-fit (GFI) index has been computed from
the LISREL software to indicate what proportion of the variance in the sample variancecovariance matrix is accounted for by the model (Jöreskog & Sorbom, 1993; Tabachnick &
Fidell, 2007). The GFI value ranges from 0 to 1 with a larger value indicating a better fit of the
model (Diamantopoulos & Siguaw, 2000). “Traditionally an omnibus cut-off point of 0.90 has
been recommended for the GFI” (Hooper, Coughlan, & Mullen, 2008, p. 54). In this study, the
GFI index is .92 (Table 3), indicating that Figure 2 provides a good platform to match the
observed covariance matrix from the real database (Diamantopoulos & Siguaw, 2000).
In addition, Byrne (1998) verified that the Comparative Fit Index (CFI) performed well
even when sample size is small. Today this index is an essential component of structural
equation modeling, and becomes one of the most popularly reported fit indices (Fan, Thompson,
& Wang, 1999; Hooper, Coughlan, & Mullen, 2008). As with the GFI, values for CFI range
between 0.0 and 1.0 with values closer to 1.0 indicating good fit. A cut-off criterion of CFI ≥
0.90 was initially advanced however, recent studies have shown that a value greater than 0.90 is
needed in order to ensure that misspecified models are not accepted (Hu & Bentler, 1999).
Again, the CFI obtained from this study is .91, which is indicative of good fit.
COEXISTING RELATIONSHIPS
27
Furthermore, “the RMSEA [Root Mean Square Errors of Approximation] favours
parsimony in that it will choose the model with the lesser number of parameters” (Hooper,
Coughlan, & Mullen, 2008, p. 54). The RMSEA is regarded as “one of the most informative fit
indices” (Diamantopoulos & Siguaw, 2000, p. 85) due to its sensitivity to the number of
estimated parameters in the model. An RMSEA in the range of .05 to .10 was considered an
indication of fair fit and values above 0.10 indicated poor fit (MacCallum, Browne, & Sugawara,
1996). In Table 3, the obtained RMSEA of .04 has positioned Figure 2 within a good fit range.
In summary, model fitting indices have been triangulated in all three major categories
recommended by researchers (Hooper, Coughlan, & Mullen, 2008; Schumacker, & Lomax,
2004). The results consistently support the model fit, regardless of the criterion choices. The
model evaluation has completely addressed the third research question for this investigation, i.e.,
empirical findings presented in this article are grounded on a solid fit to the First 5 Kern data,
rather than unsubstantiated statistical artifacts.
Conclusion
This investigation features both quantitative and qualitative inquires to examine the
coexisting relationships between the area-specific support and early childhood development. A
well-established Context, Input, Process, and Product (CIPP) paradigm has been selected from
the qualitative review of current literature to guide the quantitative data analyses. The literature
review also revealed a void in the existing knowledge on articulation of coexisting impact from
multiple service areas. The new exploration has expanded understanding of service outcomes in
four fronts:
(1) Context of Early Childhood Development
COEXISTING RELATIONSHIPS
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The ASQ indicators of early childhood development cover five aspects, i.e., gross motor,
fine motor, communication, problem solving, and personal-social skills. While height and
weight are typically used to measure muscle and bone growth in support of motor skills,
development of communication, problem solving, and personal-social skills is inseparable from
the context of environmental interaction (Piaget, 2000). This study revealed larger factor
loadings from those context-based indicators in early childhood development (Table 2).
According to Szanton (1992), "[A] newborn's brain is only about one-quarter the size of an
adult's. It grows to about 80 percent of adult size by three years of age and 90 percent by age
five” (¶. 2). It was a concurrent analysis of the multiple outcome measures that reconfirmed the
more important contributions from the contextual support.
(2) Attributes of Family Resources
Attributes of the family resources are the pre-existing conditions not to the credit of
Proposition 10 funding. However, it is an unavoidable variable at the input phase of any local
services. While affluent families have no problem to maintain healthcare coverage, children
with limited family resources tend to show a strong need of First 5 Kern support. Thus, the
family resource factor demonstrated a negative path coefficient to counterbalance the need of
early childhood services funded by Proposition 10. This result won’t be available from an
isolated investigation in which the service variables are confined among those that are alterable
by Proposition 10 funding.
(3) Process of Co-Existing Support
The support across different domains naturally occurred in daily life. As Wright, Kuo,
Regalado, and Halfon (2001) observed, “child health providers who model reading behavior and
provide books to their patients have been shown to increase the frequency and amount of reading
COEXISTING RELATIONSHIPS
29
behaviors that parents engage in with their children” (p. 6). In this example, the health care
factor coexists with the contribution of parenting effort. The joint support makes it imperative to
articulate the service process across multiple domains.
(4) Product of Priority Settings
First 5 Kern funding has been strategically planned to address priorities in multiple focus
areas (Table 1). While not all the variables carry the same weight, a predominant role has been
found from the factor of healthcare when the results incorporates the joint impact from the
process of prenatal service. Because of the alignments between the CIPP framework and the
local priority setting, the integrated model in Figure 2 has been supported by the actual data
according to critical model fit indices recommended by researchers (Hooper, Coughlan, &
Mullen, 2008; Schumacker, & Lomax, 2004).
As First 5 Kern started its services in a large geographic area with rapid population
growth, evaluation reports of its annual performance used to span more than 400 pages in the
past (e.g., Corporation for Standards and Outcomes, 2009). This investigation represents the first
effort to report concise research findings in a nationally refereed journal. Built on the modelbased approach to articulating area-specific service impacts, more variables can be incorporated
in future investigations to enrich the existing findings. For instance, cultural and ideological
factors are often embedded in parental effort regarding whether it takes a community, such as
nursery school settings, to raise children. Thus, parental attitude towar nursery education could
have been incorporated in future studies.
In addition, the annual income indicator in this study did not include extra financial
support from relatives or close friends. Still, the external support could have played a major role
in some cultures. Teachman (1987) recollected that “In most research, family background has
COEXISTING RELATIONSHIPS
30
been measured by socioeconomic indicators (e.g., parents' education, family income), to the
exclusion of other family characteristics” (p. 548). Although this investigation conformed to the
indicator choice of most research, the inclusion of more sources of family support might help
expand existing results across various cultural settings.
COEXISTING RELATIONSHIPS
31
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Table 1.
Alignment Between the State Focus Areas and Local Priorities
State Focus Area
First 5 Kern Priority Statements
Family Functioning
All parents and caregivers will be knowledgeable about early childhood
development, effective parenting and community services.
Child Health
All children will have an early start toward good health.
Child Development
Quality early childcare and education services will be accessible.
Systems of Care
A well-integrated system of services for children and families will exist.
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Table 2.
Parameter Estimates for Modeling the Relationship Between First 5 Kern Support and Early
Childhood Development
Latent Variables
Indicators
Parameter Estimates
Factor Loadings ()
Child Development
communication (ASQ score)
gross motor (ASQ score)
fine motor (ASQ score)
personal social (ASQ score)
problem solving (ASQ score)
.75
.41
.56
.72
.71
Parenting Effort
hours of weekly reading
.38
support for nursery school on regular basis .35
Health Care
regular health checkup
regular dental care
.28
.33
Family Resource
annual income
mother’s education
father’s education
.53
.84
.78
Childcare
timely prenatal care
smoke exposure
-.31
.12
Path Coefficients ()
Parenting Efforts  Child Development
.13
Health Care  Child Development
.89
Family Resource  Child Development
-.23
Childcare  Child Development
-.03
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45
Table 3.
Model Fitting Indices for the First 5 Kern Database
Model Fitting Indices
Goodness of Fit Index (GFI)
Comparative Fit Index (CFI)
Mean Square Error of Approximation (RMSEA)
First 5 Kern Results
.92
.91
.04
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46
Figure 1. CDE items on parental support for home reading and nursery education
COEXISTING RELATIONSHIPS
Support
Nursery
Schooling
47
Communication
 x1
y
y
Read to
This Child
Timely
Checkups
Dental
Care
 x2
Parenting
Effort
 x3
 x4


Mother’s
Education
Father’s
Education
y
y
y5
Personal
Social
Problem
Solving

x5
x10
x6
Fine
Motor
Health Care

Annual
Income
Child
ASQ
Score
at 36th
month
Gross
Motor
Family Resource
Childcare
 x11
x7
Figure 2. Relationships between child ASQ scores and area-specific factors.
Timely
Prenatal
Care
Smoke
Exposure