Predictors of quality and child outcomes in family child care settings

Early Childhood Research Quarterly 28 (2013) 893–904

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Early Childhood Research Quarterly

Predictors of quality and child outcomes in family child care settings Nicole Forry a,∗ , Iheoma Iruka b,1 , Kathryn Tout c,2 , Julia Torquati d,3 , Amy Susman-Stillman e,4 , Donna Bryant b,5 , M. Paula Daneri a,6 a

Child Trends, 7315 Wisconsin Avenue, Suite 1200W, Bethesda, MD, United States FPG Child Development Institute, University of North Carolina at Chapel Hill, Campus Box 8180, Chapel Hill, NC 27599-8180, United States Child Trends, 615 First Avenue NE, Minneapolis, MN 55413, United States d University of Nebraska-Lincoln, 247 Mabel Lee Hall, Lincoln, NE 68588-0236, United States e Center for Early Education and Development, University of Minnesota, 1954 Buford Avenue, Suite 425, St. Paul, MN 55108, United States b

c

a r t i c l e

i n f o

Keywords: Family child care Child care quality School readiness Professional development

a b s t r a c t Few studies have examined correlates of quality ratings in family child care arrangements. This study analyzes data from a multi-state sample of family child care providers actively seeking professional development for two purposes. First, we examine predictors of observed quality ratings focusing on characteristics of child care providers, the most proximal influences of quality in family child care. Second, we explore associations between three targets of professional development (providers’ attitudes, beliefs, and practices) and the pre-academic and social–emotional skills of preschool-aged children. Provider characteristics indicative of personal and professional resources and stress, as well as providers’ professional attitudes and beliefs, are predictive of observed quality measures. Observed quality and providers’ child-centered beliefs and perceptions of job demands are related to children’s developmental outcomes. Implications for future research, policies, and practices are discussed. © 2013 Elsevier Inc. All rights reserved.

Research addressing correlates of quality and linkages between quality and children’s developmental outcomes in family child care is sparse (Porter, Paulsell, Nichols, Begnoche, & Del Grosso, 2010; Sandstrom, Moodie, & Halle, 2011). Families with young children with sociodemographic risk factors (e.g., low-income, single parent, and limited parental education) are more likely to use home-based than center-based care (Boushey & Wright, 2004; Iruka & Carver, 2006; Snyder & Adelman, 2004). Additional research on the quality of home-based settings is needed to target professional development initiatives and support quality effectively. Family child care providers, defined in this paper as regulated, licensed, or registered caregivers who provide care for children in the caregiver’s own home, provide a significant proportion of home-based care (Iruka & Carver, 2006; Morrisey, 2007).

∗ Corresponding author. Tel.: +1 240-223-9235; fax: +1 240-200-1239. E-mail addresses: [email protected] (N. Forry), [email protected] (I. Iruka), [email protected] (K. Tout), [email protected] (J. Torquati), [email protected] (A. Susman-Stillman), [email protected] (D. Bryant), [email protected] (M.P. Daneri). 1 Tel.: +1 919 843 8085; fax: +1 919 966 7532. 2 Tel.: +1 612 331 2223x21; fax: +1 612 331 2226. 3 Tel.: +1 402 472 1674; fax: +1 402 472 0971. 4 Tel.: +1 612 624 3367; fax: +1 612 625 2093. 5 Tel.: +1 919 966 4523; fax: +1 919 966 7532. 6 Tel.: +1 240 223 9231; fax: +1 240 200 1239. 0885-2006/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ecresq.2013.05.006

A study initiated in 2004, entitled Quality Interventions for Early Care and Education (QUINCE), tested an intervention model for quality enhancement among family child care and center providers with limited education beyond high school. This paper capitalizes on the comprehensive data collected as part of this study. The purpose of this paper is not to address the effectiveness of the QUINCE intervention (for more details on this see Bryant et al., 2009). Rather, data collected as part of the QUINCE study are used to examine the associations between predictors of quality, quality indicators, and child outcomes in family child care settings, controlling for the effects of the intervention. This paper differs from previous studies of QUINCE data in a few ways. First, rather than describing the patterns of family child care providers’ quality ratings and correlates of quality using person-centered and bivariate analytic methods (Forry et al., 2012), this study uses multivariate methods to examine proximal and distal predictors of quality ratings. Second, this paper extends previously published work using the QUINCE data to examine the association between family child care providers’ professional practices and attitudes and assessments of children’s pre-academic and social–emotional skills. This study addresses two research questions related to quality in family child care settings. First, what provider-level characteristics predict observed quality practices in family child care settings? Second, are providers’ quality practices and professional attitudes and beliefs associated with children’s pre-academic and social–emotional skills? This study builds upon existing literature

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in a few ways. First, this study extends existing literature on correlates of quality in family child care settings by using process quality measures that include indicators of global quality, instructional supports, and caregiver sensitivity. These measures were selected due to their presumed alignment with child outcomes assessed through this study. Second, this study extends current knowledge regarding the link between quality and child outcomes in family child care settings by exploring associations between targets of professional development (provider attitudes, beliefs, and practices) and children’s pre-academic and social–emotional skills. This study focuses on providers’ attitudes, beliefs, and quality practices as predictors of child outcomes for three reasons. First, existing research documents the interrelations between these elements in producing high-quality care (Ajzen & Fishbein, 2005; Kontos, Howes, Shinn, & Galinsky, 1995). Second, research suggests that attitudes, beliefs, and practices are unique and malleable elements that can be influenced through professional development (Arnold, Fisher, Doctoroff, & Dobbs, 2002; Cassidy, Buell, PughHoese, & Russell, 1995; Espinosa, Mathews, Thornburg, & Ispa, 1999; Heisner & Lederberg, 2011; Todd & Deery-Schmitt, 1996). Third, professional standards published by the National Association for Family Child Care (2005) and the National Association for the Education of Young Children (n.d.) address each of these elements. Children’s literacy, math, and social–emotional skills were selected as outcomes for the second research question of this study as these skills are among the most common competencies assessed in existing state kindergarten readiness assessment systems (Daily, Burkhauser, & Halle, 2010) and have been associated with children’s later academic performance (Claessens, Duncan, & Engel, 2009; Diamond, Reagan, & Bandyk, 2000; Duncan et al., 2007; Entwisle & Alexander, 1999; Thompson & Lagattuta, 2006). 1. Predictors of quality practice in family child care Unlike center-based arrangements, family child care providers’ attitudes, beliefs, and practices are not tempered by supervision, oversight, or policies determined by others within the care environment. In essence, the quality of care offered in family child care settings is primarily defined by the provider, who designs and supplies the care environment, provides care, sets policies, and manages the family child care business. Thus, using the lens of an ecological perspective (Bronfenbrenner & Morris, 1998, 2006), the most proximal influences on quality in family child care settings are likely providers’ personal and professional characteristics. These characteristics include personal resources and stressors, professional resources (e.g., knowledge, experience), and professional beliefs. More distal influences, such as the composition of the care setting and providers’ experience of professional supports, may also influence quality. 1.1. Proximal influences on quality 1.1.1. Providers’ personal resources and stress Few studies have examined the association between family child care providers’ personal characteristics, including financial well-being and emotional health, and the quality of care they offer. Associations between provider financial well-being and quality of care are important to consider as the boundaries between family child care providers’ personal and professional lives can be unclear (Glenn, Chang, & Forcey, 1994). Financial well-being may facilitate providers’ ability to offer adequate and appropriate materials and activities, while financial stress may constrain resources or negatively impact caregiver psychological well-being. In a study of 65 licensed child care providers, Weaver (2002) found providers’ family income was positively correlated with global

quality in family child care and higher levels of personal and professional “supportive resources for child care” (p. 274). Research has also demonstrated positive associations between family child care providers’ compensation or net income (defined as income from providing care minus the direct costs of providing care) and professional commitment, provider sensitivity, and global quality measures (Helburn, Morris, & Modigliani, 2002; Weaver, 2002). No studies to date have addressed the association between family child care providers’ financial resources or income from child care and their provision of supports for early learning. Another important association to examine is between family child care providers’ mental health and quality of care. Using a sample of both center and family child care providers, Hamre and Pianta (2004) found provider depressive symptoms predicted less sensitive, more withdrawn and negative caregiving, with these associations being more robust among family child care, as opposed to center-based, providers. In studies of family child care providers only, Weaver (2002) reported that depressive symptoms negatively predicted global quality, and psychological well-being positively predicted high-quality care, but Clarke-Stewart, Vandell, Burchinal, O’Brien, and McCartney (2002) did not find an association between provider mental health and measures of instructional supports or provider responsivity. 1.1.2. Providers’ professional resources Family child care providers’ education and experience have each been associated with child care quality. Several studies have found positive associations between family child care providers’ level of general education (Burchinal, Howes, & Kontos, 2002; Marshall et al., 2003a, 2003b; NICHD Early Child Care Research Network, 2000; Raikes, Raikes, & Wilcox, 2005) and education related to early childhood (Doherty, Forer, Lero, Goelman, & LaGrange, 2006; Morrisey, 2007; Weaver, 2002) and observed global quality. Though literature associating provider education and sensitivity and/or instructional supports for quality is limited, Clarke-Stewart et al. (2002) found a positive association between educational attainment and both sensitive caregiving and the quality of the learning environment among family child care providers. Findings relating family child care providers’ experience and child care quality are less consistent. Multiple studies using assessments of global quality, provider sensitivity, and learning stimulation have found no significant association between years of experience and quality (Burchinal, Howes, et al., 2002; Clarke-Stewart et al., 2002; Doherty et al., 2006). Studies incorporating both center- and home-based child care arrangements have documented both positive (NICHD Early Child Care Research Network, 2000) and negative (Kontos et al., 1995; Phillipsen, Burchinal, Howes, & Cryer, 1997; WilcoxHerzog, 2002) associations between experience and quality. 1.1.3. Providers’ professional beliefs and attitudes Within family child care settings, providers’ progressive or child-centered beliefs have been positively related to measures of global quality, social–emotional support, and cognitive stimulation (Cassidy et al., 1995; Clarke-Stewart et al., 2002; Marshall et al., 2003a, 2003b). Additionally, family child care providers’ attitudes toward their position, as assessed by their motivation for working in child care and intention to stay in the field, has been associated with child care quality. Kontos et al. (1995) found that compared to unregulated providers, regulated family child care providers were more likely to endorse child care as their chosen occupation, report child-focused reasons for providing care, and be rated higher on observed quality measures. Doherty et al. (2006) also found intrinsic motivation for providing care (e.g., those who felt child care to be their personal calling), as compared to an extrinsic motivation (e.g., viewing child care primarily as a source of income or convenient job while their children are young), to be positively associated

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with observed global quality in family child care settings. Though Layzer and Goodson (2007) found more than half (63%) of family child care providers in the National Study of Child Care for LowIncome Families reported experiencing job-related stress, less is known about links between providers’ job stress and quality in family child care settings. Kontos and Riessen (1993) reported that job stress was inversely related to family child care providers’ job satisfaction and commitment. However, no studies to date have examined providers’ job-related stress and process quality. 1.2. Distal influences on quality practices In addition to the personal and professional characteristics of the family child care provider, there are other, more distal influences that may affect quality practices. One such influence is the composition of the care setting, which includes group size/child–adult ratio, whether a professional assistant is available in the care setting, whether residential children are in care, presence of a child with special needs, and proportion of subsidized children served. The composition of the care setting has been associated with quality in both center and home-based settings (Doherty et al., 2006; Kontos et al., 1995; NICHD Early Child Care Research Network, 2005). The most commonly examined features are group size and child–adult ratio. In studies of family child care homes, a significant association between ratio and global quality has been found in some studies (Kontos et al., 1995; NICHD Early Child Care Research Network, 2005; Raikes et al., 2005) but not in others (Burchinal, Howes, et al., 2002). Paid assistants may provide needed support and mediate against potential isolation in caring for children within a home-based setting, though no literature has tested this theory. In contrast, having a residential child in care may increase provider stress or change the dynamic of the caregiving environment. For example, Layzer and Goodson (2007) found 29% of family child care providers to perceive that their own children resented other children in care. Additional demands associated with serving children with special needs, or children with a child care subsidy, may also influence provider stress and/or the quality of the arrangement (Knoche, Peterson, Pope Edwards, & Jeon, 2006; Raikes et al., 2005). Additionally, in family child care, use of support services, such as belonging to a professional organization or network, informally networking with other providers, and using community resources (e.g., library story hour or a toy lending library) have been associated with higher scores on measures of global quality and provider sensitivity (Bromer, van Haitsma, Daley, & Modigliani, 2009; DeBord & Sawyers, 1995; Doherty et al., 2006; Pence & Goelman, 1991). 2. Associations between targets of professional development and child outcomes Little has been published on associations between quality and child outcomes in family child care. With few exceptions (Clarke-Stewart et al., 2002), studies that address these associations aggregate findings from center and family child care arrangements (NICHD Early Child Care Research Network, 2000). In this study, we extend current research by adding to the body of knowledge associating quality in family child care to child outcomes and expanding predictors of child outcomes to include not only observed quality practices, but also providers’ beliefs and attitudes about their profession. The inclusion of both quality practices and beliefs and attitudes as predictors of child outcomes reflects recently published conceptualizations of quality (Bromer et al., 2011) as well as literature distinguishing provider attitudes, beliefs, knowledge, and practices as unique and interrelated targets of professional development (Ajzen & Fishbein, 2005). It should be noted that knowledge

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is omitted as a predictor of child outcomes in this study due to the lack of a reliable indicator of providers’ professional knowledge at the time of the QUINCE study. 2.1. Providers’ beliefs, attitudes, and practices and child outcomes Research to date has not reported upon associations between providers’ professional attitudes and beliefs and children’s developmental outcomes. However, there is literature positively associating family child care providers’ child-centered motivation and quality practices (Doherty et al., 2006; Kontos et al., 1995). Additionally, though no research has examined the association between providers’ progressive beliefs and children’s outcomes, parents’ child-centered, progressive beliefs about childrearing have been positively associated with children’s academic skills (Burchinal, Peisner-Feinberg, Pianta, & Howes, 2002; Campbell, Goldstein, Schaefer, & Ramey, 1991; Murphey, 1992). Measures of quality practices, assessing both global quality and provider sensitivity and responsiveness, have been significantly associated with children’s attachment and cognitive development (Galinsky, Howes, & Kontos, 1995). These relations hold across ethnic/racial groups and were similar for regulated, non-regulated, and relative home-based providers. Using an observational measure of quality developed for the NICHD Study of Early Child Care (ORCE), Belsky et al. (2007) found that higher child care quality, regardless of type, positively predicts children’s vocabulary in sixth grade, even after controlling for family demographics. Caregiver sensitivity has also been positively associated with children’s language and cognitive development (Hirsh-Pasek & Burchinal, 2006). Additionally, Kryzer, Kovan, Phillips, Domagall, and Gunnar (2007) reported structured care environments that are sensitive and supportive to be positively associated with children’s social integration, attention/engagement, and positive mood. de Schipper, Riksen-Walraven, Geurts, and Derksen (2008) also found caregiver positivity and optimism to be positively associated with children’s expressions of satisfaction and happiness. Only one study, to date, has examined associations between instructional supports and child outcomes in home-based settings. Using the ORCE, Clarke-Stewart et al. (2002) reported that children enrolled in family child care homes that were more cognitively stimulating performed better on assessments of language, cognitive, and social development than children in less cognitively stimulating arrangements. 3. Summary In summary, the depth of knowledge regarding predictors of process quality in family child care settings is mixed, with more research focusing on measures of global quality than provider sensitivity or instructional supports. Though there is research to support associations between some provider characteristics and process quality in family child care settings (e.g., child-centered beliefs), other provider characteristics have an underdeveloped research base (e.g., providers’ financial well-being, experience of depressive symptoms, and perceptions of job demands). Given the under-developed literature in family child care settings relative to research on center-based settings, new findings examining the array of quality correlates in family child care are warranted. Additionally, limited literature is available on associations between providers’ professional attitudes, beliefs, and observed quality in family child care settings and child outcomes. Our study addresses this gap in the literature by considering providers’ attitudes toward their position, child-centered beliefs, and quality practices as predictors of children’s pre-academic and social–emotional skills.

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4. Hypotheses We predict that providers’ personal and professional resources, and professional attitudes (e.g., intrinsic motivation and commitment to their profession) and beliefs (e.g., child-centered beliefs) will be positively associated with observed process quality. We also hypothesize that indicators of personal or professional stress will be negatively associated with observed process quality. Regarding associations between providers’ attitudes, beliefs, and practices and measures of children’s pre-academic and social–emotional skills, we offer a few hypotheses. First, we predict that indicators of providers’ attitudes, beliefs, and practices will each be uniquely predictive of child outcomes. Second, we hypothesize that associations between observed quality practices and children’s skills will be conceptually aligned. For example, the quality care and teaching composite measure is expected to positively predict children’s early literacy and math skills, whereas sensitive caregiving is expected to positively predict children’s social–emotional health and negatively predict children’s internalizing/externalizing behavior problems.

5. Method 5.1. Participants The data used in this paper come from the Quality Interventions for Early Care and Education (QUINCE) study (Bryant et al., 2009), an experimental evaluation of a consultation-based professional development intervention for child care providers. The QUINCE study includes multi-state data from provider surveys, quality observations, and child assessments. The analyses presented in this paper do not address the impact of the QUINCE intervention. Rather, membership in the intervention group was controlled in all levels of our analytic model. Recruitment for this study occurred in five states: California, Iowa, Minnesota, Nebraska, and North Carolina. A two-tiered recruitment strategy was used. First, professional development consultants from 24 agencies that provided quality enhancement services for child care programs were recruited to the study. Consultants were randomly assigned to either the intervention or a control group that offered quality enhancement activities typically provided by their agencies. Second, center providers and family child care providers who were seeking quality enhancement services from one of the 24 participating agencies were recruited and randomly assigned to intervention or control consultants. A comparison group of center and family child care providers was also recruited to provide a contrast for the analyses of change over time in quality. A total of 347 family child care providers from the control, comparison, and treatment groups are included in the QUINCE sample. Reflective of the QUINCE study design, this sample is comprised primarily of providers with less than a Bachelor’s degree. Additionally, the QUINCE study did not restrict participation to licensed family child care providers due to differences in the study states’ licensing regulations, though 96% of participating participants were either registered or licensed. Recruitment of children occurred approximately six months after providers began participating in the QUINCE study. Children in the sample had been cared for in the participating family child care home for at least six months prior to the child assessment, were between the ages of 20 months and five years, and spoke English or Spanish as their native language. Eligible children were recruited through their providers, with an average of two children per family child care arrangement (max of six children). A total of 699 children cared for by family child care providers were included in the QUINCE study.

Quality observation and survey data were collected at entry into the study (Time 1) and approximately ten months later (Time 2). Assessments of children’s pre-academic and social–emotional skills and behaviors in the care arrangement were collected approximately six months after providers’ Time 2 observation and survey. For additional information on the QUINCE study design and data collection, see Bryant et al. (2009). 5.1.1. Sample selection The sample for analyses summarized in this paper was limited to family child care providers from the QUINCE study who were serving children between the ages of 2.5 and 5 years. This selection criterion was used to reflect the appropriate age range for selected child assessments. Of the 347 family child care providers who completed an interview and quality observations at Time 1 or Time 2, 58% (N = 202) met this criteria. Of these 202 providers, six had missing data from either the provider interview or observation and an additional 14 were missing child demographic/assessment data. Providers with missing data (about 10% of the sample) were dropped, yielding a total analytic sample of 182 providers. Missing data were not accounted for via imputation or Full Information Maximum Likelihood as the missing data patterns violated assumptions of non-random distribution and attrition of the sample was systematic. Providers who were excluded from the analytic sample due to missing data differed from providers in the analytic sample on only one characteristic: provider-reported depressive symptoms. Whereas only 10% of providers in the analytic sample reported experiencing depressive symptoms, 31% of providers who were eliminated from the analytic sample due to missing data reported having depressive symptoms (t = 3.03, p ≤ .01). All of the home-based providers included in our analytic sample were female. Most of the providers were White (71%), equal proportions were African American (12%) and Latino (12%), and the remaining reported being either Asian or “other” race. Over threequarters of the sample were married and living with their spouse. Approximately 90% spoke English as their primary home language and the remaining 10% either spoke primarily Spanish or a mixture of English and Spanish at home. Additional characteristics of providers are summarized in Table 1 and discussed in Section 5.2. A total of 451 children between the ages of 2.5–5 years with complete child assessments were included in these analyses. Sixteen percent were Latino, 11% African American, 66% White, and 7% other, which included biracial and multi-racial children. Twenty-two percent of children in the sample had subsidized care. Fifty-seven percent of the children were male and the average age of children was 3.64 years (SD = .69). 5.2. Measures In order to minimize bias related to missing data and obtain more reliable measurements of observed quality and potentially time-variant features of the care arrangement, composite scores that average provider survey data and observational quality measures collected at Time 1 and Time 2 were used. The practice of averaging scores over two time points to obtain more reliable measurements is consistent with prior research (Burchinal, Vandergrift, Pianta, & Mashburn, 2009; Weinfield, Sroufe, & Egeland, 2000). Child assessments were conducted approximately six months after the second provider survey/quality observation. 5.2.1. Provider survey Providers were interviewed in their home shortly after the provider entered the study (Time 1) and again at the conclusion of the intervention (Time 2). The interview included questions about professional development experiences, attitudes, beliefs,

N. Forry et al. / Early Childhood Research Quarterly 28 (2013) 893–904 Table 1 Descriptive statistics on key variables. M (SD) Proximal predictors of quality Providers’ personal resources Income-to-needs ratio Providers’ professional resources Education Years of experience Providers’ beliefs and attitudes Progressive beliefs about childrearing Professional motivation Intention to stay in field Providers’ personal/professional stress Depressive symptoms Provider perception of job demands Distal predictors of quality Composition of the care setting Number of children regularly in care Subsidy density Child with special needs in care Residential child in care Paid assistant Provider professional supports Encouragement from others Frequency of communication with other home-based providers Member of professional organization Child care quality Quality care and teaching FDCRS total score ECERS-E literacy score CIS sensitivity score Child outcomes Pre-academic skills Positive emotional health Problem behaviors

Range

3.00 (1.40)

.55–7.79

13.12 (1.51) 10.45 (8.74)

8–16 0–37

53.78 (9.02) 4.38 (.47) 4.06 (.77)

26–78 2.36–5 1.50–5.00

.10 (.24) 2.68 (.53)

0–1 1.50–4.33

6.28 (2.38) 0.18 (0.27) 0.40 (0.49) 0.47 (0.50) .28 (.41)

1–14 0–1 0–1 0–1 0–1

.60 (.49) 1.58 (1.03)

0–1 0–3

.50 (.45)

0–1

2.76 (.72) 3.48 (.81) 2.11 (.54) 2.94 (.49)

1.37–6.02 1.65–5.37 1.17–5.08 1.65–3.85

101.72 (17.09) 3.86 (.59) 2.07 (.58)

62–146 1.74–5 1–4.20

Note: N = 182 (providers); N = 451 (children).

behaviors, mental health and job stress, and demographic questions (e.g., education, work experience, and personal characteristics). Several questions about the composition and characteristics of the family child care providers’ programs were also included. 5.2.1.1. Proximal correlates of quality. Providers’ personal resources. Provider income-to-needs ratio (INR) was calculated as a measure of financial well-being by dividing the provider’s reported family income by their family’s size, reflecting the methodology used to create percentages of the federal poverty threshold (FPL). Rather than multiplying by 100 to present INR as a percentage of the federal poverty threshold, the INR is reported as a raw decimal. For example, an INR of 1 means a family is at the poverty threshold and an INR of 2 signifies that a family is at twice the poverty threshold. The average income-to-needs ratio for providers in our sample was 3.00 (SD = 1.40, range = .55–7.79). Providers’ professional resources. Family child care providers were asked how many years of education they completed. Provider responses ranged from 8 to 16 years of education (M = 13.12, SD = 1.51). The QUINCE study sampled providers with limited education beyond high school. As only 16% of the sample had education specific to early childhood, we did not include an indicator for this characteristic in our model. Providers’ years of experience in child care reflects their response to the following question “In total, how many years have you worked in child care, since you were 18 years old (including all types of child care)?” Providers in our analytic sample had between < 1 and 37 years of experience (M = 10.45, SD = 8.74). Providers’ beliefs and attitudes. Family child care providers’ beliefs about childrearing were assessed with the Parent Modernity Scale (Schaefer & Edgerton, 1985). This 16-item scale measures

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providers’ “traditional” (or authoritarian) and “progressive” (or child-centered) views regarding the care of children on a response scale ranging from 1 (strongly disagree) to 5 (strongly agree). Examples of traditional beliefs are “children will not do the right thing unless they are told what to do” and “the most important thing to teach children is absolute obedience to whoever is in authority.” Examples of progressive, or child-centered, beliefs are “children have a right to their own point of view and should be allowed to express it” and “children learn best by doing things themselves rather than listening to others.” The total score used in the analyses ranges from 24 to 78 and is based on reverse-scoring of the traditional subscale combined with the progressive subscale. Higher scores represent more child-centered, progressive childrearing beliefs. Developers report positive correlations with parental education and income, as well as child academic and social competence and intelligence (Schaefer & Edgerton, 1985). Internal consistency within the analytic subsample for the total modernity score was .60 compared to .73 for the full QUINCE family child care sample. The mean score for this sample was 53.78 (SD = 9.02). Professional motivation of family child care providers was assessed with 11 items adapted from a study of family child care providers (Kontos et al., 1995). These items relate to providers’ job perceptions and satisfaction with their position. Due to a low Cronbach’s alpha among family child care providers in our analytic sample for items indicating provider satisfaction (˛ = .50), we included only the seven professional motivation items (˛ = .73) in this study, which include whether the provider perceives his/her job as a paycheck or a career, feels he/she is making a difference with their work, and how respected he/she feels. Providers rated each item on a 5-point scale, ranging from 1 (not at all the way that I feel) to 5 (exactly the way that I feel). An average score on the Professional Motivation subscale was calculated, with higher scores indicating more motivation to be a child care provider (M = 4.38; SD = .47). A second measure of professional motivation, provider intention to stay in the field, was assessed using the following question: “For about how many more years do you plan to be a child care provider?” Categorical response options ranged from 1 (<1 year) to 5 (>10 years). Providers in our analytic sample intended to stay in the field, on average, 5–10 years. The professional motivation subscale and intention to stay in the field were moderately correlated (r = .38; p = .001). Indicators of personal or professional stress. Provider report of depressive symptoms was assessed using three items comprising a brief depression screener (Rand, 1998). Providers reported how frequently within the past 12 months he/she felt “sad”, “empty”, or “depressed”. Providers who answered two of three questions positively were coded as experiencing depressive symptoms on a binary variable (1 = yes, 0 = no). Ten percent of providers in our analytic sample reported experiencing depressive symptoms. A 21-item scale, using items from the Child Care Worker Job Stress Inventory (Curbow, Spratt, Ungaretti, McDonnell, & Breckler, 2001) assessed perceptions of job demands. This inventory demonstrates strong concurrent validity with other measures of role control, overload, and insufficiency (Curbow et al., 2001). Though this 21item scale has four subscales (Job Demands, Job-Specific Demands, Job Rewards/Resources, and Job Control), only the Job Demands subscale was used for this study as the face validity of items on this subscale best reflected our construct of interest. The six items that comprise the job demands subscale include questions regarding interactions with parents, handling children’s challenging behaviors, and responding to multiple children’s needs at the same time. Internal consistency for the Job Demands subscale was .66 for the full QUINCE family child care sample and .51 for our analytic sample. Items were rated on a scale ranging from 1 (never) to 5 (most of the time). An average score on this subscale was calculated, with higher scores indicating greater perceived demands by the provider

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(M = 2.68; SD = .53). Providers’ report of depressive symptoms and perceptions of job demands were significantly but modestly correlated (r = .11, p = .01).

5.2.1.2. Distal correlates of quality. Composition of the care setting. Five characteristics of the child care setting were obtained from the provider interview: number of children in care at least 20 h per week, proportion of children served whose care was subsidized (subsidy density), whether a child with special needs was in the care setting, whether any of the children in care live with the provider, and whether the provider had a paid assistant. Providers in the analytic sample had an average of six children in care (SD = 2.38, range = 1–14). Subsidy density was calculated by dividing the number of subsidized children, according to provider report, by the total number of children in care. On average, 18% of children in each family child care arrangement had a child care subsidy. A dichotomous variable reflecting whether a provider served any children with special needs (1 = yes, 0 = no) was based on the following question: “How many children have a special need that requires additional care when they are in your home?” Examples of special needs included health needs or disabilities, speech or language delays, behavior problems, learning disabilities, limited English proficiency, or special dietary/nutrition needs. Forty percent of providers reported caring for at least one child with a special need. The presence of residential children in care was determined by asking providers how many children live with them and receive care in their home. Due to a positive skew in the continuous count of residential children in care, this measure was dichotomized with “0” indicating no residential children and “1” indicating at least one residential child in care; just under half (47%) of providers cared for a residential child. Finally, a dichotomous variable indicating whether a provider had a paid assistant (1 = yes, 0 = no) was calculated based on the following question: “Do you have any regular paid assistants who care for children directly on a regular basis, age 16 or older, for [the] family child care home?” Approximately three-tenths (28%) of providers had a paid assistant. Professional supports. Three provider professional supports were assessed: encouragement from child care professionals, frequency of speaking with other family child care providers, and belonging to a professional organization. Providers were asked if they received encouragement in their development as a child care provider from any of the following sources: provider support network, co-worker, supervisor, or local child agency. Responses were summed, but due to the positive skew in the distribution of a continuous measure of sources of encouragement, a dichotomous variable was created to differentiate receipt of encouragement (1) from no perceived encouragement (0). Sixty percent of providers reported receiving encouragement from someone in the child care field. Frequency of communication with other family child care providers was assessed by asking providers “In a typical week, how many times do you talk on the phone or in-person with other family child care providers?” Scores on this categorical variable are 0 (never), 1 (once/week), 2 (2–4 times per week), and 3 (more than 4 times per week). Providers in the analytic sample, on average, communicated with other providers between one and four times per week (M = 1.58, SD = 1.03). Providers were asked if they were current members of various early childhood and education associations (e.g., National Association for the Education of Young Children [NAEYC], National Association for Family Child Care [NAFCC], Division of Early Childhood [DEC]). A dichotomous variable was created indicating membership in at least one professional organization (1) or no memberships (0); fifty percent of providers reported being in a professional organization. Correlations between each of these three support variables were statistically significant and ranged from r = .21 to r = .36.

5.2.2. Child care quality observations Observational measures of the family child care environment were collected upon provider entry into the study (Time 1) and again approximately 10 months later (Time 2). Measures included a global quality assessment, the Family Day Care Rating Scale (FDCRS; Harms & Clifford, 1989); an assessment of instructional supports, the Early Childhood Environment Rating Scale – Extension (ECERSE; Sylva, Sirai-Blatchford, & Taggart, 2006); and an assessment of provider sensitivity in the child-caregiver relationship, the Caregiver Interaction Scale (CIS; Arnett, 1989). For each measure, scores from both data collection time points were averaged to produce a composite score. Observers maintained an acceptable level of reliability across measures, as summarized through the following kappa statistics. The average inter-rater reliability for the FDCRS was .80 and ranged from .68 to .93; the ECERS-E was .72 and ranged from .58 to .93; and the CIS was .68 and ranged from .63 to .80. Correlations on the observed quality measures across the two data collection waves ranged from r = .44 to .60 and the quality care and teaching and caregiver sensitivity ratings were correlated at r = .62, p = .001. 5.2.2.1. Quality care and teaching. Due to the high correlation between the FDCRS measure and ECERS-E items included in this analysis (r = .82, p ≤ .001), a composite score of quality care and teaching was created. This score was calculated by averaging the FDCRS and ECERS-E total scores described below across the fall and spring administrations of each instrument (˛ = .89; M = 2.76; SD = .72). 5.2.2.2. Family Day Care Rating Scale (FDCRS). The FDCRS is an observational rating scale used to assess global quality in the family child care environment. This rating has 38 items divided into seven subscales: (1) Space and Furnishings for Care and Learning, (2) Personal Care Routines, (3) Listening and Talking, (4) Learning Activities, (5) Social Development, (6) Program Structure, and (7) Adult Needs. To be consistent with other research, the Adult Needs items were not included in the overall family child care quality scores (Clifford et al., 2005; Early et al., 2005; Snow et al., 2007). Each item is rated on a seven-point scale with scores ranging from 1 (inadequate practices) to 7 (excellent practices). The average total global quality rating for providers in the sample was 3.48 (SD = .81), which falls into the “minimal” range of quality (˛ = .88). 5.2.2.3. Early Childhood Environmental Rating Scales-Extension (ECERS-E). The ECERS-E was developed to supplement global environmental rating scales, specifically for use in British preschool programs. Strong relationships have been documented between ECERS-E and ECERS-R (r = .78) and the ECERS-E and CIS Positive Relationship subscale (r = .59) (Sylva et al., 2006). Sylva et al. (2006) also found a positive relation between the ECERS-E and children’s literacy, math, and non-verbal reasoning. Following consultation with the measure developers to ensure applicability of this measure in home-based settings, the ECERSE was included in the QUINCE study in order to assess provider facilitation of early literacy and math skills, both of which were central to the QUINCE intervention. The QUINCE data collectors completed this measure on the same day as the FDCRS. Parallel to the FDCRS, scores ranged from 1 (inadequate practices) to 7 (excellent practices). Seven observation items from the ECERS-E were used to assess instructional supports for early literacy. These items specifically assessed the book and literacy area, adults reading with children, and environmental print. Four items from the ECERS-E were used to assess instructional supports for early math. These items specifically assessed reading and representing simple numbers. The internal reliability for the ECERS-E literacy and mathematics subscales combined for this sample was good (˛ = .82). The

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average rating on the supports for early learning subscale in this sample was 2.11 (SD = .54), which is between “inadequate” and “minimal” quality. 5.2.2.4. Caregiver Interaction Scale (CIS). The CIS is an observational measure of the interactions between providers and the children in their care and has been positively related to global quality (Arnett, 1989) and children’s outcomes (Hirsh-Pasek & Burchinal, 2006). The CIS includes 26 items rated on a scale from 1 (not at all), to 4 (very much). Four dimensions of the providers’ interactions are assessed: Sensitivity, Harshness, Detachment, and Permissiveness. For this study, ten items from the Sensitivity subscale were used. Items assessing warmth, responsivity, and positive affect of providers were averaged to create the Sensitivity subscale rating. This subscale was selected for inclusion in our model because it had the highest internal reliability of the CIS subscales (˛ = .89) and most closely reflected of our construct of interest- provider sensitivity. The average rating on provider sensitivity in this sample was 2.94 (SD = .49), or “quite a bit” sensitive. 5.2.3. Child developmental outcomes Children were assessed by trained data collectors on their preacademic skills using the school readiness composite of the Bracken Basic Concepts Scale-Revised (BBCS-R; Bracken, 1998) and by their child care providers on their social–emotional skills and behaviors using subscales of the Devereux Early Childhood Assessment (DECA; LeBuffe & Naglieri, 1999). Assessments occurred during the fall in the year after providers’ Time 2 quality observation and surveys. The magnitude of correlations between children’s pre-academic skills and both their social–emotional skills (r = .125, p = .05) and problem behaviors (r = −.165, p = .01) were small. 5.2.3.1. Literacy and mathematics pre-academic skills. The BBCS-R is used for children ages 2.5–6. Reliability and validity information provided in the Bracken manual report internal consistency coefficients ranging from .93 to .97 for preschool-age children and a test–re-test reliability of .88 (Bracken, 1998). The school readiness composite also demonstrated strong concurrent validity with the Verbal, Performance, and Full Scale IQ of the Wechsler Preschool and Primary Scale of Intelligence-Revised with correlations ranging from .76 to .88 (Bracken, 1998). The first six subtests of this instrument, which include knowledge of literacy and mathematical concepts, specifically Colors, Letters, Numbers, Sizes, Comparisons, and Shapes, were administered by trained child assessors. The subtests are summed to provide a total pre-academic score, which is then converted into a standard score. Standardized scores are categorized as follows: 0–69 (very delayed), 70–84 (delayed), 85–115 (average), 116–130 (advanced), and 131–150 (very advanced). In this study, children’s standardized pre-academic scores ranged from 62 to 146 (M = 101.72, SD = 17.09), with a value of 100 indicating average school readiness skills. 5.2.3.2. Provider-rated social–emotional skills and behaviors. The DECA is a 37-item, 5-point Likert-scale that measures the frequency of select behaviors in the past four weeks among 2- to 5-year old children. In addition to correlating in the expected direction with similar measures, criterion validity of the DECA indicates good precision in clinical diagnosis for problem behavior (LeBuffe & Naglieri, 1999). The two broad areas of the DECA are Total Protective Factors (called Positive Emotional Health in this study), which measures initiative, self-control, and attachment; and Total Behavioral Concerns (called Internalizing/Externalizing Problem Behaviors in this study), which measures withdrawal/depression, emotional control problems, attention problems, and aggression. Response scales range from 1(never) to 5 (frequently). Positive emotional health scores ranged from 1.74 to 5.00 (M = 3.86, SD = .59), with higher scores

899

reflecting more evidence of positive emotional indicators (˛ = .88). Internalizing/externalizing problem behaviors scores ranged from 1 to 4.2 (M = 2.07, SD = .58), with higher scores indicating more evidence of problem behaviors (˛ = .84).

5.3. Analytic technique We used a multi-level modeling technique to simultaneously address our two research questions. The model was run using maximum-likelihood estimation in Mplus® (Muthen & Muthen, 2006), a statistical software package created for latent variable modeling. A nested design was used to cluster children into their family child care settings. Level 1 of the model used children as the unit of analysis. In this segment of the model, children’s school readiness skills and behaviors were predicted by select indicators of providers’ attitudes, beliefs, and quality practices, controlling for child demographic characteristics obtained from the parent consent form and a dichotomous indicator of whether or not the provider was in the intervention group. Specifically, children’s pre-academic literacy and mathematical skills, positive emotional health, and internalizing/externalizing behavior problems were each regressed on providers’ child-centered beliefs, providers’ job stress, and the two observed quality practice measures (quality care and teaching and provider sensitivity). These Level-2 predictors were selected to represent three interdependent targets of professional development that may have unique influences on children’s experience in care and, consequently, their skills and behaviors. Statistical controls included children’s age, gender, whether the child was receiving a child care subsidy (a conservative proxy for low family income), and provider intervention status. The intraclass correlation coefficients indicated that nesting within family child care settings accounted for 13% of the variability in Bracken scores, 33% for positive emotional health scores, and 30% for problem behavior scores. Level 2 of the model focused on predictors of observed quality in family child care settings with providers serving as the unit of analysis. Within this level, observed measures of process quality, specifically quality care and teaching and provider sensitivity, were regressed on a series of ecologically-organized features. The primary foci of the Level 2 model were indicators conceptualized as proximal influences on quality: providers’ personal and professional resources and stress, professional beliefs, and attitudes. More distal influences on quality controlled for in the model included the composition of the child care arrangement and supports external to the care environment. As with Level 1, a statistical control for intervention status was included.

6. Results 6.1. Model fit As this model does not include latent variables, model fit was assessed using the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR). These fit indices are used in accordance with recommendations by Bentler and Bonett (1980), Brown and Cudeck (1993), and Hu and Bentler (1999). The RMSEA statistic is used to approximate the fit of the model to the population with values of .05 or less acceptable as evidence of providing good fit. Similarly the SRMR measures the standardized difference between the observed covariance and predicted covariance. A value of zero indicates perfect fit with a value less than .08 considered a good fit. Joint RMSEA/SRMR criteria for adequate model fit proposed by Hu and Bentler (1999) are:

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Table 2 Path coefficients predicting to quality of care. Quality care and teaching

Proximal influences on quality Personal resources Personal financial resources Professional resources Provider education Years of experience Provider attitudes/beliefs Child-centered beliefs Intrinsic professional motivation Intention to stay in the field Indicators of stress Depressive symptoms Job demands Distal influences on quality Composition of the care setting Number of children in care Residential child in care Subsidy density Child with special needs Paid assistant Professional supports Communication with other home-based providers Received encouragement Professional organization Controls Treatment status

Arnett sensitivity

ˇ

B

SE

ˇ

B

SE

.11*

.05

.03

.12

.04

.03

−.01 .15

−.01 .01

.03 .006

.08 .15*

.02 .01

.02 .004

.17** .25*** −.05

.01 .35 −.04

.005 .10 .07

.19** .14* .001

.01 .14 .00

.004 .08 .05

−.07 −.23**

−.20 −.29

.18 .09

−.06 −.13

−.12 −.12

.13 .06

−.04 −.14 −.002 −.08 .03

−.01 −.19 −.005 −.10 −.05

.02 .10 .20 .09 .12

−.27** −.12 −.01 −.01 .02

−.05 −.12 .01 −.01 .03

.02 .07 .14 .07 .10

−.04 .04 .23***

−.02 .05 .34

.04 .10 .10

.01 .10 −.06

.01 .10 −.06

.04 .08 .08

.02

.02

.08

−.06

−.06

.07

R2 = .32

R2 = .20

Note: Model fit indices: RMSEA = .06; SRMRwithin = .005; SRMRbetween = .10; Nchildren = 451; Nproviders = 182. * p ≤ .05. ** p ≤ .01. *** p ≤ .001.

RMSEA ≤ .06 and SRMR ≤ .09. The fit indices for the analytic model are RMSEA = 0.06; SRMRwithin = 0.005; SRMRbetween = 0.10. 6.2. Research question 1: predictors of process quality 6.2.1. Proximal correlates of quality Table 2 presents the regression coefficients related to our first research question. As predicted, providers’ personal financial resources positively predicted quality care and teaching (ˇ = .11, p ≤ .05). Providers’ personal financial resources were not associated with their observed sensitivity toward children. One indicator of professional resources, providers’ years of experience, was positively associated with sensitive caregiving (ˇ = .15, p ≤ .05). Provider experience was not a significant predictor of quality care and teaching, nor was provider education associated with either quality rating. Two of the three indicators of provider attitudes and beliefs were significant predictors of both quality ratings. Specifically, provider report of an intrinsic, child-focused motivation for providing care was positively associated with observed quality care and teaching (ˇ = .25, p ≤ .001) and sensitivity (ˇ = .14, p ≤ .05). Additionally, child-centered, or progressive beliefs about children, as assessed by Schaefer and Edgerton’s (1985) modernity scale, were positively associated with both quality measures (ˇquality care and teaching = .17, p ≤ .01; ˇsensitive caregiving = .19, p ≤ .01). No statistically significant associations were found between providers’ intentions to stay in the field and quality. Of the indicators of providers’ personal or professional stress examined in this study, a negative association was found between providers’ perception of job stress and quality care and teaching (ˇ = −.23, p ≤ .01). No statistically significant associations were found between provider depressive symptoms and either quality measure.

6.2.2. Distal correlates of child care quality Among features reflecting the composition of the care setting included in our model, only one statistically significant association was found. The number of children in the care setting was negatively associated with providers’ sensitivity (ˇ = −.27, p ≤ .01). Features of the family child care arrangement that were not statistically associated with either quality rating included the presence of a paid assistant, residential or special needs child in care, and subsidy density. One of the provider supports tested in our model was positively related to the quality care and teaching rating: membership in a professional organization (ˇ = .23, p ≤ .001). No associations were found between provider report of encouragement, or frequency of communication, and either quality rating. Likewise, none of the provider supports were statistically significant predictors of the caregiver sensitivity quality rating. 6.3. Research question 2: associations between providers’ attitudes, beliefs, and quality practices and children’s developmental outcomes Regression coefficients related to our second research question are presented in Table 3. As predicted, providers’ attitudes, beliefs, and practices, three interrelated targets of professional development, were each uniquely associated with at least one of the three child outcomes examined. The most consistent predictor of child outcomes was observed quality care and teaching, which was positively associated with children’s pre-academic literacy and math skills (ˇ = .38; p ≤ .05) and emotional health (ˇ = .50; p ≤ .001) and negatively associated with children’s internalizing/externalizing behavior problems (ˇ = −.31; p ≤ .05). Providers’ child-centered beliefs were positively associated with children’s pre-academic literacy and math skills (B = .36; p ≤ .001). Finally, a positive

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Table 3 Path coefficients predicting to child outcomes. Six months post quality observations and provider surveys Bracken school readiness ˇ Attitudes Job demands Knowledge/beliefs Child-centered beliefs Quality practices Quality care and teaching Arnett-sensitivity Controls Treatment status Subsidy receipt Child’s age Child’s gender

B

Positive emotional health

SE

ˇ

B

SE

−.08

.08

.04

.73

1.89

−.13

.36***

.35

.11

.03

5.01 −1.49

2.13 2.98

.50*** −.17

3.24 −12.72 2.61 −4.51

1.95 3.29 1.64 1.78

.00 −.05 .17*** −.22***

.38* −.08 .18** −.23*** .12 −.15** 2 Rwithin = .09 2 Rbetween = .31

* ** ***

Internalizing/externalizing problem behaviors

2 Rwithin = .08 2 = .23 Rbetween

ˇ .26**

B

SE .16

.07

.004

−.16

−.01

.004

.24 −.11

.07 .08

−.31* .22

−.15 .15

.06 .08

.00 −.09 .13 −.23

.07 .11 .04 .06

.08 .02 −.06 .23***

.06 .03 −.04 .23

.07 .09 .04 .05

.001

2 Rwithin = .06 2 = .19 Rbetween

p ≤ .05. p ≤ .01. p ≤ .001.

association was found between providers’ perceptions of job demands and their rating of children’s problem behaviors (B = .26; p ≤ .01). No significant associations were found between ratings of caregiver sensitivity and children’s pre-academic skills, emotional health, or behavior problems. 7. Discussion The purposes of this paper were to identify predictors of observed process quality in family child care settings and associations between three targets of professional development (provider attitudes, beliefs, and practices) and measures of children’s preacademic and social–emotional school readiness. In predicting observed process quality, we focused primarily on personal and professional resources, stressors, attitudes, and beliefs of family child care providers. We hypothesized these to be the most proximal influences on quality because of the dual role of family child care providers as the provider and director of their program. More distal predictors (e.g., composition of the care setting and professional supports external to the care setting) were also examined as predictors of quality. Before discussing the results of our study, it is important to note that the sample for this study consisted of family child care providers actively seeking professional development. This is an important distinction because, though our sample is not representative of all family child care providers, the providers in this sample may be similar to those who voluntarily participate in state professional development systems. 7.1. Proximal correlates of process quality This paper offers new information regarding associations between family child care providers’ personal and professional resources and stress, professional attitudes and beliefs, and their ratings on observed process quality measures. Evidence was found to support most of our hypotheses regarding correlates of quality practices. We found that providers’ personal financial resources are positively associated with global and instructional quality, though the magnitude of this relationship is small (d = .07). This is a meaningful addition to extant research addressing the blur in personal and professional boundaries among family child care providers (Glenn et al., 1994) as it suggests that some providers may use

their personal financial resources to meet both personal (family) and professional (child care) demands. Only partial evidence was found to support our prediction that professional resources would be positively associated with observed process quality ratings. Specifically, a positive association was found between provider experience and caregiver sensitivity. It should be noted that null findings regarding the association between provider education and observed measures of process quality may reflect the uneven distribution of providers in our sample, 22% of whom had only a high school degree and 84% of whom had only two years of education beyond high school. This null finding is not consistent with previous literature, which has found both education and early childhoodspecific education to be positively predictive of quality ratings (Burchinal, Howes, et al., 2002; Marshall et al., 2003a, 2003b; Raikes et al., 2005; Weaver, 2002). Most of the provider attitudes and beliefs included in our model were predictive of both quality care and teaching and provider sensitivity. Providers who reported more child-centered, progressive caregiving beliefs and higher levels of intrinsic motivation were rated, on average, as offering higher global and instructional quality and more sensitive caregiving. These associations are consistent with extant literature (Cassidy et al., 1995; Clarke-Stewart et al., 2002; Kontos et al., 1995; Kontos & Riessen, 1993) and add support to the theory that provider attitudes, beliefs, and practices are closely interrelated (Ajzen & Fishbein, 2005). No statistically significant associations were found between providers’ intentions to stay in the field and their quality ratings. As more than one-half of providers in our sample reported an intention to stay in the field at least five years, this null finding may be explained by the limited variability in the provider intentions variable. Finally, some evidence was found to support our prediction that indicators of providers’ stress are negatively associated with observed quality ratings. Consistent with our hypothesis, providers’ report of job demands was negatively associated with ratings of quality care and teaching. This finding fills an important gap in the literature regarding provider stress and child care quality. However, it is surprising that providers’ perception of job stress was not statistically associated with their sensitivity toward children. This null finding may reflect a lack of sensitivity to detect an association, due to limited variation on the caregiver sensitivity measure. Contrary to our hypotheses, no statistically significant associations

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were found between providers’ depressive symptoms and quality ratings. It should be noted that only ten percent of providers in this sample reported experiencing depressive symptoms, and a greater proportion of providers who were dropped from these analyses due to missing data on key variables reported depressive symptoms than those included in the analytic model. 7.2. Distal correlates of process quality Controlling for proximal predictors of quality, only two of the features conceptualized as distal influences on child care quality were predictive of observed process quality ratings. Number of children in care was negatively associated with caregiver sensitivity and participation in a professional organization was positively associated with quality care and teaching practices. The relative dearth of significant associations between distal features and quality indicators is consistent with our assumption that characteristics of the provider are more closely associated with quality in family child care settings than features of the care setting or professional supports.

(˛ = .5–.6) in our analytic sample. These scales were included in our analyses due to their face validity and use in prior research. Second, among providers in our sample, quality ratings on the Quality Care and Teaching measure do not reflect the full range of possible scores. Specifically, the average rating was in the “minimal” range of quality, few providers were rated as providing “good” care, and none were rated as providing “excellent” care. This restricted range of quality may have implications for the generalizability of our findings. Specifically, the findings of this study may shed light on predictors of higher quality among mediocre quality providers, rather than predictors of high quality care. Second, a disproportionate proportion of providers with self-reported depressive symptoms were dropped from this study due to missing data. As only 10% of providers in the analytic sample had reported experiencing depressive symptoms, we had limited power to detect associations between providers’ experience of depressive symptoms and observational measures of process quality. Likewise, the measures for provider education, provider intention to stay in the field, and caregiver sensitivity had either skewed distributions or limited variation, which may have affected study findings.

7.3. Predictors of child outcomes 7.4. Implications for practice, policy, and future research This study offers new information about the associations between unique, but interrelated, targets of professional development and children’s pre-academic and social–emotional outcomes. Evidence was found for positive associations between each of the professional development targets – provider attitudes, beliefs, and practices – and at least one of the outcomes examined. The observed measure of global and instructional quality practices was the most consistent predictor of child outcomes, positively predicting children’s school readiness and emotional health and negatively predicting children’s problem behaviors. These associations were small to moderate in magnitude (dBracken = .29, dbehavior problems = .26, dpositive emotion = .41), which is consistent with previous research (Burchinal, Kainz, & Cai, 2011). It should be noted that children’s emotional health and behavior problem ratings were based on provider report. Thus, the moderate effect size reflecting the association between quality care and teaching and children’s positive emotional health may, at least partially, reflect differences in how higher quality providers rate children’s emotional health. Contrary to our predictions, provider sensitivity was not a significant predictor of any of the child outcomes. Though we did not expect providers’ sensitivity to be as strongly related to children’s pre-academic skills as quality care and teaching, the lack of a significant association between providers’ sensitivity and children’s emotional health and problem behaviors is surprising. This null finding may be related to the limited variation on the caregiver sensitivity measure. Associations were detected between both provider attitudes and beliefs and child outcomes. First, providers’ perceived job demands were positively associated with providers’ ratings of children’s behavior problems. Causal inferences and the direction of this association cannot be determined. It may be that providers caring for children with behavior problems perceive their job as more demanding or that providers who are stressed have a lower tolerance for undesired behaviors and thus are more likely to rate children as having behavior problems. Second, a positive association was found between providers’ child-centered beliefs and assessments of children’s pre-academic skills. This association is consonant with literature from center-based settings (Barbarin, Downer, Odom, & Head, 2010). Though this study adds unique information to the relatively small body of research addressing quality in family child care, it does have a few limitations worthy of mention. First, the reliabilities of the job demands and child-centered belief scales were low

Findings from this study suggest a few possible directions for future policies and practices regarding correlates of quality in family child care arrangements. For example, though it is likely unrealistic to offer family child care providers an income supplement, the positive association between providers’ personal resources and global/instructional quality suggests small grant programs may be helpful in supporting low-income providers to purchase materials and equipment needed to offer a comfortable and enriching learning environment. Additionally, the findings of this study related to provider attitudes, beliefs, quality practices, and child outcomes suggest that further research is needed to identify effective delivery methods and content of professional development that addresses both quality practices and providers’ professional attitudes and beliefs. Future studies can build upon findings from existing studies on the effectiveness of changing providers’ attitudes and beliefs through reflective supervision (Virmani & Ontari, 2010), professional development (Arnold et al., 2002; Cassidy et al., 1995; Espinosa et al., 1999; Heisner & Lederberg, 2011; Todd & Deery-Schmitt, 1996), partnerships with Early Head Start programs (Buell, Pfister, & Gamel-McCormick, 2002), and family child care networks (Bromer et al., 2009). Future research on the associations tested in this study is encouraged. Researchers are specifically encouraged to build upon findings from this study related to providers’ personal financial resources and job-related stress, as existing literature on these characteristics is sparse. Also, future research is needed to replicate and extend this study with samples that reflect the heterogeneity of the family child care provider population. Finally, more nuanced examinations of associations detected in this study are recommended. Specifically, future research could address potential mediators or moderators for associations detected in this study. For example, among center-based providers, intrinsic professional motivation has been linked to features of the center, such as the supervisor-staff relationship and co-worker relations (Wagner & French, 2010). Though we know that professional motivation varies among family child care providers (Porter et al., 2010), we have little knowledge of correlates of intrinsic motivation. Additionally, the positive association between providers’ child-centered beliefs and pre-academic skills may be mediated by the specific opportunities and interactions children have with providers. Identifying and developing measures that are sensitive to these opportunities/interactions could be used to extend the breadth of existing

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quality measures and refine indicators of quality specified in professional standards and Quality Rating and Improvement Systems. 7.5. Conclusion In conclusion, this study offers new information regarding correlates of quality in family child care and associations between providers’ attitudes, beliefs, and quality practices and child outcomes. Both personal and professional characteristics of family child care providers predicted global and instructional quality and sensitive caregiving. Additionally, associations were found between providers’ child-centered beliefs, perceptions of job demands, and quality practices and children’s pre-academic and social–emotional skills. Research that replicates and expands upon the findings of this study is recommended. Acknowledgments The authors acknowledge the Administration for Children and Families for their support of the QUINCE project (grant # 90YE0056) and thank Dr. Martha Zaslow and Dr. Rebecca Starr for their input into earlier drafts of this paper. References Ajzen, I., & Fishbein, M. (2005). The influence of attitudes on behavior. In D. Albarracin, B. T. Johnson, & M. P. Zanna (Eds.), The handbook of attitudes (pp. 173–222). Mahwah, NJ: Erlbaum. Arnett, J. (1989). Caregivers in day-care centers: Does training matter? Journal of Applied Developmental Psychology, 10, 541–552. Arnold, D. H., Fisher, P. H., Doctoroff, G. L., & Dobbs, J. (2002). Accelerating math development in Head Start classrooms. Journal of Educational Psychology, 94, 762–770. Barbarin, O. A., Downer, J. T., Odom, E., & Head, D. (2010). Home-school differences in beliefs, support, and control during public pre-kindergarten and their link to children’s kindergarten readiness. Early Childhood Research Quarterly, 25, 358–372. Belsky, J., Burchinal, M., McCartney, K., Vandell, D. L., Clarke-Stewart, A., & Owen, M. T. (2007). Are there long-term effects of early child care? Child Development, 78, 681–701. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness-of-fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–600. Boushey, H., & Wright, J. (2004). Working moms and child care. Washington, DC: Center for Economic and Policy Research. Bracken, B. (1998). Bracken School Readiness Assessment. San Antonio, TX: Harcourt Assessment. Bromer, J., Paulsell, D., Porter, T., Henly, J., Ramsburg, D. M., Weber, R., et al. (2011). Family sensitive caregiving: A key component of quality in early care and education arrangements. In M. Zaslow, I. Martinez-Beck, K. Tout, & T. Halle (Eds.), Quality measurements in early childhood settings (pp. 161–190). Baltimore MD: Brookes. Bromer, J., van Haitsma, M., Daley, K., & Modigliani, K. (2009). Staffed support networks and quality in family child care: Findings from the Family Child Care Network Impact Study. Chicago, IL: Local Initiatives Support Corporation. Bronfenbrenner, U., & Morris, P. A. (1998). The ecology of developmental processes. In W. Damon, & R. M. Lerner (Eds.), Handbook of child psychology: Vol. 1. Theoretical models of human development (pp. 993–1028). Hoboken, NJ: Wiley. Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner, & W. Damon (Eds.), Handbook of child psychology: Vol. 1. Theoretical models of human development (pp. 793–828). Hoboken, NJ: Wiley. Brown, M. W., & Cudeck, R. (1993). Alternate ways of assessing model-fit. In K. A. Bollen, & K. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage. Bryant, D., Wesley, P. W., Burchinal, M., Sideris, J., Taylor, K., Fenson, C., et al. (2009). The QUINCE-PFI study: An evaluation of a promising model for child care provider training: Final report. Chapel Hill, NC: FPG Child Development Institute. Buell, M. J., Pfister, I., & Gamel-McCormick, M. (2002). Caring for the caregiver: Early Head Start/family child care partnerships. Infant Mental Health Journal, 23, 213–230. Burchinal, M., Howes, C., & Kontos, S. (2002). Structural predictors of child care quality in child care homes. Early Childhood Research Quarterly, 17, 87–105. Burchinal, M., Kainz, K., & Cai, Y. (2011). How well do our measures of quality predict child outcomes? In M. Zaslow, I. Martinez-Beck, K. Tout, & T. Halle (Eds.), Quality measurement in early childhood settings (pp. 11–32). Baltimore, MD: Brookes. Burchinal, M., Peisner-Feinberg, E., Pianta, R., & Howes, C. (2002). Development of academic skills from preschool through second grade: Family and classroom predictors of developmental trajectories. Journal of School Psychology, 40, 415–436.

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