Development of the Home Executive Function Environment (HEFE) Scale: Assessing its relation to preschoolers' executive function

Early Childhood Research Quarterly 47 (2019) 9–19

Contents lists available at ScienceDirect

Early Childhood Research Quarterly

Development of the Home Executive Function Environment (HEFE) Scale: Assessing its relation to preschoolers’ executive function夽 Irem Korucu ∗ , Emily Rolan, Amy R. Napoli, David J. Purpura, Sara A. Schmitt Purdue University, Human Development and Family Studies, 1202 W. State Street, West Lafayette, IN 47907, United States

a r t i c l e

i n f o

Article history: Received 20 December 2017 Received in revised form 1 June 2018 Accepted 5 September 2018 Keywords: Home environment Executive function Parenting practices Home-EF environment scale Preschool

a b s t r a c t Executive function (EF) skills are important for the development of children’s school readiness and academic achievement. One important context where children may develop these skills is the home environment, and research has found that broad indicators of the home environment and parenting practices are related to the development of children’s EF. However, it is also important to investigate whether parents’ EF-specific practices with their children (e.g., playing concentration games) are related to children’s EF skills. In this study, we developed the Home EF Environment (HEFE) scale and analyzed it using factor analysis with a sample of 120 preschool children and one of their parents in the Unites States. Mean age for children ranged from 38 to 69 months (M = 56.65, SD = 6.54), and 52% were male. Additionally, we analyzed the associations between the parent-reported HEFE scale and children’s EF skills. Factor analysis indicated that EF-specific activities form a distinguishable part of the home environment. Further, a set of hierarchical regression analyses indicated that the HEFE scale is related to a global measure of children’s EF over and above the home learning environment and general parenting practices, but not cognitive flexibility or inhibitory control. The potential importance of EF-specific activities in the home environment as well as study implications is addressed in the discussion. © 2018 Elsevier Inc. All rights reserved.

Children’s executive function (EF) has received considerable attention in the last several years as a key indicator of a host of developmental and health outcomes, including school readiness, academic achievement, social–emotional competence, and physical health (Best, Miller, & Naglieri, 2011; Moffitt et al., 2011; Riggs, Jahromi, Razza, Dillworth-Bart, & Mueller, 2006; Schmitt et al., 2017). As such, there has been an increased interest in identifying factors that may be related to growth in this set of skills, particularly during the preschool period when rapid development in EF is most evident (Bell & Deater-Deckard, 2007; Garon, Bryson, & Smith, 2008). The home environment has been identified as a critical context where EF develops (Bradley & Corwyn, 2002). Previous research suggests that general parenting practices such as sensitivity and responsiveness, as well as demographic characteristics such as maternal education, are related to children’s EF (Blair, Protzko, & Ursache, 2011; Sektnan, McClelland, Acock, & Morrison, 2010). However, researchers have yet to explore the extent to which parent-reported, EF-specific home practices (e.g., concentration games) are associated with children’s EF. The dearth of research

夽 This project is supported by a grant from the Clifford B. Kinley Trust (Award Number: 208424). ∗ Corresponding author. E-mail address: [email protected] (I. Korucu). https://doi.org/10.1016/j.ecresq.2018.09.001 0885-2006/© 2018 Elsevier Inc. All rights reserved.

in this area may be because there is no extant measure of EF-specific activities in the home, or a home EF environment scale. Thus, the primary aims of the current study are 1) to evaluate if engaging in EF-specific activities is a distinct aspect of the home environment, specifically by analyzing the recently developed Home EF Environment (HEFE) scale using factor analysis; and 2) to explore the association between the HEFE scale and children’s EF. 1. The importance of EF EF is defined as a complex and interrelated set of cognitive processes including working memory (holding and manipulating information in mind), cognitive flexibility (ability to shift attention and to think in multiple ways), and inhibitory control (suppressing behavior, thought, and attention) that are utilized in planning, problem solving, and goal directed thoughts (Garon et al., 2008; Zelazo, Blair, & Willoughby, 2016). Two theoretical approaches have been proposed regarding the dimensionality of EF. Some research suggests that EF is a unitary construct (Hughes, Ensor, Wilson, & Graham, 2010), while others suggest it is a multidimensional construct (Lerner & Lonigan, 2014; Lonigan, Lerner, Goodrich, Farrington, & Allan, 2016). Although both perspectives have received empirical support, in this study, we conceptualize EF as a set of related, yet dissociable cognitive skills (Friedman & Miyake, 2017; Garon et al., 2008; Zelazo et al., 2016).

10

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

EF starts to develop in infancy and becomes more coordinated during the preschool years due to rapid development of the prefrontal cortex between ages 2 and 5 (Zelazo, Craik, & Booth, 2004; Zelazo & Muller, 2011). A large body of evidence suggests that EF is critical for school success and later life outcomes, including physical health and personal finances (Blair, 2002; McClelland et al., 2007; Moffitt et al., 2011). Research has shown that EF during preschool is particularly important as it predicts early math and literacy skills, as well as future academic performance, above and beyond early academic skills (Blair & Razza, 2007; McClelland, Acock, Piccinin, Rhea, & Stallings, 2013; Ursache, Blair, & Raver, 2012). In addition, children with better EF skills at early ages have been shown to display more social–emotional competence and fewer problem behaviors in later years (Hughes & Ensor, 2008; Lewis & Carpendale, 2009; Razza & Blair, 2009). 2. Individual differences in EF Children enter school with varying levels of EF (Blair, 2002; Sektnan et al., 2010; Wanless, McClelland, Tominey, & Acock, 2011). Some research suggests that individual differences in EF stem from biological and temperamental factors (Friedman et al., 2008); however, some evidence indicates that individual differences in EF are more strongly associated with aspects of children’s environments (Lapointe, Ford, & Zumbo, 2007; Zelazo et al., 2016), such as the quality of the home and school contexts (Bernier, Carlson, Deschenes, & Matte-Gagne, 2012). Developmental systems theory supports the importance of examining the role of contextual factors for the development of EF. This theory emphasizes that the development of EF occurs in a relationally integrated person-context system, and a child’s development of EF depends on dynamic interactions between her or his characteristics and the nature of the environment (McClelland et al., 2018). Additionally, EF development is linked to the prefrontal cortex and is found to be relatively plastic and responsive to environmental influences as early as 3 and 4 years of age (Diamond, 2013). This plasticity in EF is particularly relevant from an educational standpoint because improvements in EF may positively influence a wide variety of developmental outcomes. Given its importance and links with later development, there is a strong interest in the malleability of EF skills and strategies for promoting them, especially for preschool children (Zelazo et al., 2016). Strategies and interventions for improving EF have been identified in the school environment, and several intervention programs have focused on promoting children’s EF and attention skills. For instance, Rueda, Rothbart, McCandliss, Saccomanno, and Posner (2005) demonstrated that practice on game-like tasks (i.e., a child version of the Flanker task; the Attention Network Task [ANT]) is related to improvements in EF. Similarly, an evaluation of a preschool intervention provided evidence for improvements in children’s EF when their teachers received training on effective classroom strategies and frequent coaching support (Raver et al., 2011). Other large and small group activities implemented in classrooms, such as mindfulness exercises, music and movement, and stop-think-act games, have also been identified as successful strategies for improving children’s EF skills (Flook, Goldberg, Pinger, & Davidson, 2015; Schmitt, McClelland, Tominey, & Acock, 2015; Winsler, Ducenne, & Koury, 2011). Although the evidence is mixed, some recent work has indicated that these intervention gains in EF also transfer to other skills such as academic outcomes (Schmitt et al., 2015). 3. The home environment In contrast to the school environment, few strategies and interventions have been empirically evaluated in the home context.

Despite this lack of empirical evidence, theoretical work suggests that the home environment is a critical context where children’s EF develops (Bradley & Corwyn, 2002). 3.1. The home learning environment The home learning environment, in particular, may be an important indicator of EF. The home learning environment is broadly defined as characteristics of the home setting that may contribute to children’s learning. It encompasses both proximal parenting practices (e.g., educational activities) and more distal practices such as providing learning materials at home (Bradley & Caldwell, 1995). The home learning environment has been shown to have strong positive relations with early academic outcomes, as well as later educational attainment (Bradley, Burchinal, & Casey, 2001; Melhuish et al., 2008). The home learning environment is typically measured by the amount, frequency, and nature of the activities that parents create for children (Sénéchal & LeFevre, 2002; Son & Morrison, 2010). When parents engage their children in enriching activities such as reading, writing together, and playing board games, children demonstrate better vocabulary and academic skills (Rodriguez & Tamis-LeMonda, 2011; Son & Morrison, 2010). In particular, the quality of the home environment—assessed by the common comprehensive measure of the home context, Home Observation for Measurement of the Environment (HOME; Caldwell & Bradley, 1984)—is associated with children’s development, including language, academic, and social skills (Fantuzzo, McWayne, Perry, & Childs, 2004; Sénéchal & LeFevre, 2002; Votruba-Drzal, 2003). Further, domain-specific aspects of the home learning environment, including the home literacy and numeracy environments, are predictors of language, literacy, and math outcomes (Manolitsis, Georgiou, & Tziraki, 2013; Schmitt, Simpson, & Friend, 2011). In terms of EF development, the majority of research exploring the role of the home environment has focused on general parenting practices (e.g., parenting style; Fay-Stammbach, Hawes, & Meredith, 2014), housing characteristics (e.g., residential mobility; Schmitt et al., 2015), or family background (e.g., maternal education; Sektnan et al., 2010). Although this work suggests that broader aspects of the home environment support or hinder children’s EF development, little is known regarding whether EF-specific activities in the home are related to preschoolers’ EF. 3.2. Parenting and EF 3.2.1. General parenting practices related to EF One characteristic of the home environment that has been well studied with regard to EF is parent-child interaction (Bernier et al., 2012). Children are dependent on their caregivers for stimulation, nurturance, and regulation during their early years of life (Sameroff, 2010). During this initial relationship with the caregiver, children learn to regulate their attention and emotions, which is argued to provide a foundation for the development of EF (Kopp, 1989; Zelazo et al., 2016). Parenting is a complex construct including distinct aspects (e.g., warmth, support for autonomy, stimulation, intrusiveness) that can be grouped into general positive and negative factors. These broad positive and negative factors have been shown to be associated with individual differences in children’s EF (Blair et al., 2011). Specifically, Landry and Smith (2010) introduced four theoretically-derived dimensions of parenting behaviors that may be associated with children’s EF: scaffolding, stimulation, sensitivity-responsivity, and control-discipline. Empirical studies also demonstrate that these aspects of parenting practices (e.g., sensitivity-responsivity) are linked to better EF in children (Bernier, Carlson, & Whipple, 2010). Among these different dimensions of

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

parenting practices, most studies have focused on the role of parental scaffolding and sensitivity-responsivity. Parental scaffolding is defined as parents’ verbal or nonverbal efforts to help their children with a challenging activity while supporting their autonomy, choices, and decisions (Lewis & Carpendale, 2009). Research examining the role of parental scaffolding for EF has revealed that scaffolding (e.g., support during problem solving) is positively related to children’s EF both concurrently (Bibok, Carpendale, & Muller, 2009) and longitudinally (Hammond, Müller, Carpendale, Bibok, & Liebermann-Finestone, 2012; Hughes & Ensor, 2008; Landry, Miller-Loncar, Smith, & Swank, 2002; Lengua, Honorado, & Bush, 2007). In addition, one specific aspect of maternal scaffolding—support for autonomy—is positively related to differences in EF in young children, even after controlling for other dimensions of positive parenting such as sensitivity and mind-mindedness (Bernier et al., 2010). Parental stimulation includes parent-child engagement in enriching activities (e.g., shared book reading). Empirical studies show that parental stimulation is positively linked to children’s EF and a lack of such support in the home is linked to delays in EF (Clark et al., 2013). Parental sensitivity-responsivity involves being attentive and accurately responding to children’s signals (Bernier et al., 2012). Several longitudinal studies suggest that maternal sensitivity-responsivity is also positively associated with EF in early childhood (Bernier et al., 2012; Blair et al., 2011; National Institute of Child Health and Human Development [NICHD], 2005). Supportive control involves using positive discipline strategies, such as providing reasons why rules should be obeyed (Fay-Stammbach et al., 2014). Although there is limited research, longitudinal evidence suggests that lower levels of parental behavioral control are linked to increases in children’s EF (Bindman, Hindman, Bowles, & Morrison, 2013). All of these four dimensions of parenting behaviors are assumed to promote the development of EF in children because encouragement of children’s decisions, the provision of enriched interactions, and support during productive activities are all argued to promote the internationalization of children’s regulatory capacities, which leads to better EF skills (Kopp, 1989; Landry & Smith, 2010). 3.2.2. Parent–child games and activities related to EF Although identifying general parenting practices that are related to EF is important, no studies to date have explored whether more narrowly defined, EF-specific games and activities in the home are distinct from general parenting practices, and whether these activities are related to EF above and beyond general practices. To address this, we developed the Home EF Environment (HEFE) scale, which is comprised of items reflecting activities in the home that may support children’s EF. The scale consists of five items. One item reflects concentration activities that children may engage in at home (e.g., puzzles) that may facilitate EF development. In intervention studies, engagement with game-like concentration tasks has been show to promote children’s EF (Rueda et al., 2005; Thorell, Lindqvist, Nutley, Bohlin, & Klingberg, 2009). In addition, we developed several items related to music and movement activities that parents may engage in with their children. Research has shown that music and movement activities are effective strategies in classroom settings for improving growth in children’s EF. For example, in one study, children who were enrolled in a structured musical curriculum that included singing and dancing demonstrated better EF compared to children who were not enrolled (Winsler et al., 2011). In another set of studies, participation in music and movementbased circle time games that required children to stop, think, and then act supported growth in EF (Duncan, Schmitt, & McClelland, 2017; Schmitt et al., 2015; Tominey & McClelland, 2011). An example of one of these circle time activities is a game called Red Light, Purple Light. In this game, modified from the popular chil-

11

dren’s game Red Light, Green Light, children are expected to respond differently to specific cues given by their teacher who acts as a stoplight (e.g., first purple means stop and orange means go, then the rules change and purple becomes go and orange becomes stop). Another HEFE item represents the frequency of children’s physical activities. There is some intervention (Davis et al., 2011) and correlational research (Campbell, Eaton, & McKeen, 2002) showing that engagement in physical activities (e.g., aerobic exercise) is linked to better EF skills in children (Best, 2010; Tomporowski, Lambourne, & Okumura, 2011). Finally, we included an item in the scale that represented engagement in memory games as participation in these types of activities may facilitate the development of EF, and particularly working memory (Thorell et al., 2009). A primary goal of the present study was to explore whether these identified EF-specific activities that may be occurring in the home are related to preschool children’s EF. Research has shown that when parents explicitly engage their children in math-related and literacy-related activities at home, their children show greater levels of math and literacy development (Evans, Shaw, & Bell, 2000; LeFevre et al., 2009). Thus, the practice of EF-related activities in the home may be related to EF development above and beyond other general and specific parenting practices such as scaffolding and sensitive parenting. 4. The present study Given that EF skills are malleable and show improvement with intervention programs (Zelazo et al., 2016), it is important to identify practices parents engage in at home with their children that may be related to EF. However, to our knowledge, no research has investigated the possible association between EF-related activities in the home and children’s EF above and beyond the home learning environment and general parenting practices. In the current study, we had two aims: 1) analyzing the HEFE scale using factor analysis to evaluate if engaging in EF-specific activities is a distinct aspect of the home environment and 2) exploring the association of the HEFE scale with children’s EF. On the basis of previous theoretical and empirical evidence (Bernier et al., 2010; Landry & Smith, 2010), we hypothesized that EF-related activities would be a separate factor, distinct from the four general parenting factors. Further, we hypothesized that EF-related activities would be positively associated with children’s EF above and beyond the home learning environment and other parenting practices. 5. Method 5.1. Participants Participants were 120 preschool children and one of their parents from the Midwestern region of United States. Children ranged in age from 38 to 69 months (M = 56.65, SD = 6.54), and 52% were male. Three-fourths (77.2%) of the participants were Caucasian, 4.7% Hispanic, 4.7% Asian, 2.4% African American, 6.3% Multiracial, and 4.7% were not reported. The breakdown of parent education was as follows: some high school (5%), General Education Diploma (GED; high school equivalency certificate; 6%), high school diploma (17%), some college (18%), associate’s degree (8%), bachelor’s degree (22%), master’s degree (13%), and doctoral degree (9%). The mean level of parents’ education was some college experience, meaning that parents had at least one year of college experience, but they did not attain a college degree. 5.2. Procedures We collected data from children and parents at one time point during the preschool year. We recruited participants from

12

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

18 community-based preschools and Head Start centers selected through convenience sampling. Parents of all children between ages 3 and 5 at participating preschools were sent home a letter with a description of the study and invitation to participate. Prior to participation, parents provided written consent. Parents completed short demographic surveys, the HEFE scale, and a separate scale measuring the home learning environment and their general parenting practices adopted from the Parent Behavior Inventory (Lovejoy, Weis, O’Hare, & Rubin, 1999) and the Parenting Practices Questionnaire (Robinson, Mandleco, Olsen, & Hart, 1995; Robinson et al., 1996). Trained research assistants directly assessed children’s EF skills in quiet spaces at children’s preschools that took approximately 20 min to complete. After the participation, all parents received a $20 gift card.

they saw a picture of a moon and “sun” when they saw a picture of a sun. Children were timed to see how many pictures they could correctly respond to in 45 s. Next, they were asked to repeat the task, but were told to say the opposite of the picture instead (i.e., “moon” for pictures of the sun and “sun” for pictures of the moon). In both trials, children were not allowed to continue to the next picture until they responded to the previous picture correctly. In both trials 1 and 2, when a child incorrectly responded, he or she was first asked, “What do you say for this one?” In trial 2, children were reminded “This is the opposites game” if they continued to respond incorrectly. A variable that represented the number of items completed on the “opposite” trial in 45 s was used in statistical models. This task has strong test-retest reliability and is highly correlated with other measures of inhibitory control (Archibald & Kerns, 1999).

5.3. Measures 5.3.1. Executive function Three direct assessments were used to measure children’s EF, including a card sorting task based on the Three-Dimensional Change Card Sort (DCCS; Zelazo, 2006), the Head-Toes-KneesShoulders (HTKS; McClelland et al., 2007), and the Sun-Moon task (Archibald & Kerns, 1999). 5.3.2. Card shorting task We used a card sorting task based on the DCCS (Zelazo, 2006) to measure children’s cognitive flexibility. In this task, children were asked to sort picture cards based on three different dimensions—shape, color, and size—with each dimension consisting of six items. First, children were asked to sort on the basis of shape. Then, the rule changed and children were asked to sort on the basis of color. Next, children were asked to sort on the basis of size. Children were awarded 1 point for each correct response. If children scored 5 or more points on the third section (i.e., sizesorting items), a fourth set of six items was administered with a more complex rule. For these items, children were asked to sort on the basis of size when a card included a thick black border, and to sort on the basis of color when the card did not have a thick black border. Children were given one point for each correct response, with scores ranging from 0 to 24. This measure has shown strong psychometric properties in previous research (McClelland et al., 2014). 5.3.3. Head–Toes–Knees–Shoulders (HTKS) The HTKS is a behavioral assessment of global EF that taps the integration of working memory, attentional flexibility, and inhibitory control and is administered in three phases (McClelland et al., 2014; McClelland & Cameron, 2012). In the first phase, children were asked to respond naturally to a command (e.g., “Touch your head”). Then children were asked to do the opposite of the original instruction (e.g., “Instead of touching your head, you touch your toes.”). In phases two and three, the complexity of the task was increased by adding commands and rules (e.g., “Touch your knees”). The measure consists of 30 items, with a range in scores from 0 to 60. Children were given a score of 0 for an incorrect response, a 1 for a self-corrected response, and a 2 for a correct response. Past research has indicated that the HTKS has high inter-rater reliability ( > .90) and validity with diverse samples (McClelland et al., 2007, 2014; Wanless, McClelland, Acock, Chen, & Chen, 2011). Cronbach’s alpha for the current sample was .84. 5.3.4. Sun/Moon task We used the Sun/Moon task, a modified Stroop-like task, to assess children’s inhibitory control (Archibald & Kerns, 1999). Children were shown a page with pictures of suns and moons in a 5 × 6 layout. In the first trial, children were asked to say “moon” when

5.3.5. Home environment We measured three aspects of children’s home environment— the home learning environment, general parenting practices, and the home EF environment—using self-report questionnaires. 5.3.6. Home learning environment (HLE) Parents provided ratings of how frequently their children engaged in 10 activities with them in the past month. The items (e.g., printing letters, engaging in math activities, reading story books) were included to measure the general HLE. Parents were asked to rate each behavior on a 6-point Likert scale (0 = never, 1 = 1–3 times a month, 2 = about once a week, 3 = 2–5 times per week, 4 = daily, 5 = multiple times a day). Internal consistency was .83 for all 10 items. 5.3.7. General parenting practices We provided parents with a list of 15 parenting practices reflecting Landry and Smith’s (2010) four parenting dimensions (i.e., scaffolding, stimulation, sensitivity-responsivity, and controldiscipline). Items were derived from the Parenting Practices Questionnaire (Robinson et al., 1995, 1996) and Parent Behavior Inventory (Lovejoy et al., 1999). The Parenting Practices Questionnaire has good psychometric properties and is argued to appropriately reflect Baumrind’s authoritative, authoritarian, and permissive typologies (Robinson et al., 1995). Only items from authoritative typology were chosen for this study based on previous research on parenting and children’s EF. The authoritative typology consisted of four factors: warmth and involvement (e.g., I give praise when my child is behaving), reasoning-induction (e.g., I explain the consequences of his/her behavior to my child), democratic participation (e.g., I allow my child to give input into family rules), and good natured-easy going (e.g., I show respect for my child’s opinion by encouraging him/her to express them). In addition, several items from the Parent Behavior Inventory were modified and included in the general parenting practices questions (e.g., I try to teach my child new things). We asked parents to rate each behavior on a 5-point Likert scale (1 = never/I don’t do this; 2 = once in a while, 3 = about half of the time, 4 = very often, 5 = always/I always do this; see Table 1 for a complete list of items). 5.3.8. Home EF Environment (HEFE) scale The research team developed items reflecting EF-specific games and activities after completing a review of recent EF literature. The goal was to identify observable behaviors or activities of parents that may support the development of EF. We gave particular attention to recent EF intervention work where particular activities promoted the development of different components of EF (Davis et al., 2011; Duncan et al., 2017; Thorell et al., 2009; Winsler et al., 2011). After the initial development of the HEFE scale, members of

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

13

Table 1 Standardized factor loadings for dimensions of the home environment. Item My child and I spend time playing games, doing crafts, or doing other activities. I try to teach my child new things. I allow my child to give input into family rules. I encourage my child to freely express himself/herself even when disagreeing with me. I take my child’s desires into account before asking him/her to do something. I explain the consequences of his/her behavior to my child. I give my child reasons why rules should be obeyed. I give praise when my child is behaving. I comfort my child when s/he seems scared, upset or unsure. I listen to my child’s feelings and try to understand them. I am responsive to my child’s feelings or needs. I help, or offer to help, my child with thins s/he is doing. When making plans for the family, I take into account my child’s preferences. I play games that require my child to stop, think, then act (e.g., Red Light, Green Light). I play memory games with my child. I play games with my child that require concentration and attention (e.g., puzzles). I sing songs with my child that repeat and add on to earlier sections with words or motions (e.g., she’ll be coming around the mountain when she comes). I encourage my child to engage in physical activity for at least 30 min per day.

Stimulation

Sensitivityresponsivity

Controldiscipline

Warmth

EF-specific activities

Cronbach’s alpha if item deleted

.81 .78 .78 .64 .70 .78 .95 .38 .61 .73 .70 .59 .67 .74

.69

.69 .71

.71 .71

.62

.74

.44

.79

the research team who are experts in EF reviewed the items. Following minor modifications in wording, the development of the HEFE scale consists of five items reflecting parents’ specific EFpractices at home was complete. The five items include: “I play games that require my child to stop, think, then act (e.g., Red Light, Green Light)”; “I play memory games with my child”; “I encourage my child to engage in physical activity for at least 30 min per day”; “I play games with my child that require concentration and attention (e.g., puzzles)”; and “I sing songs with my child that repeat and add on to early sections with words of motions (e.g., She’ll be coming around the mountain when she comes).” We asked parents to rate each behavior on a 5-point Likert scale (0 = never/I don’t do this, 1 = once in a while, 2 = about half of the time, 3 = very often, 4 = always/I always do this). Cronbach’s alpha was .77 for all five items and alphas representing the scale if an item was deleted were presented in Table 1.

els and compared them with the five-factor model that assumes four parenting factors and the HEFE represent five separate factors. Then, we conducted separate hierarchical linear regression analyses for each of the three measures of EF (i.e., card sorting task, HTKS, and Sun/Moon) in IBM SPSS Statistics 24. To investigate the association between the HEFE factor and EF, we ran the first set of hierarchical regression analyses with child’s age, parent education, and child’s gender in step one and the HEFE factor in step two for each of the three direct assessments of EF (Model 1). To examine if EF-specific activities were a significant predictor of EF above and beyond the HLE (i.e., reading story books, printing letters) and general parenting factors (i.e., stimulation, sensitivity-responsivity, control-discipline, and warmth), in the second set of hierarchical regression analyses we entered child’s age, parent education, child’s gender in step one, the HLE and general parenting factors in step two, and the HEFE factor in step three (Model 2).

5.4. Analytical strategies

6. Results

To evaluate if engaging in EF-specific activities (HEFE scale items) is a distinct aspect of the home environment, we conducted a confirmatory factor analysis (CFA) using items from both the HEFE and the general parenting practices scale with full information maximum likelihood in R (Revelle, 2016). We used CFA instead of EFA because the items were pulled from previously used and validated measures. The CFA confirmed a five-factor structure for the data, as detailed below. Factors were labeled stimulation, sensitivity-responsivity, control-discipline, warmth, and EF-specific activities. Once the factors were confirmed, we exported factor scores derived from the CFA and tested alternative models to examine whether our newly developed EF-specific activities formed a distinct factor. First, we created a one-factor model by allowing all of the items to load onto one factor assuming that four parenting factors and the HEFE represent only one factor. We also tested a two-factor model by allowing all general parenting items to load onto one factor and EF-specific activities item to another factor assuming that parenting factors and the HEFE represent two separate factors. We examined fit indices of these alternative mod-

Descriptive statistics and bivariate correlations for study variables are presented in Table 2. The HEFE factor was positively associated with the HLE and all other parenting factors. All of the components of EF (i.e., card-sorting task, HTKS, and the Sun/Moon task) were positively associated, and unexpectedly the card-sorting task was negatively associated with parental stimulation factor. All measures of EF were normally distributed. The factor loadings are presented in Table 1. Hierarchical regression analyses are presented in Tables 3 and 4. 6.1. Are EF-specific activities a distinct factor of the home environment? Goodness of fit indices were evaluated using Hu and Bentler’s (1999) criteria that suggest good fit when SRMR values are less than .08, RMSEA values are less than .06, and CFI and TLI values are close to or greater than .95. The expected fivefactor model was identified and fit indices for the model were: 2 (125) = 185.26 p < .001, SRMR = .07, RMSEA = .06, CFI = .92, TLI = .90

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

30.75 (8.53) 9–54 −.02 .12 21.21 (17.14) 0–55 .20 −1.14 14.82 (6.54) 2–22 −.48 −1.49 2.75 (.72) 1–4 −.11 −.28 3.56 (.42) 2.2–4 −.73 −.30

.35***

3.40 (.55) 2–4 −.67 −.04

–

.32**

– −.15 .15 −.03 – .55*** −.18 .02 .04 – .49*** .41*** −.05 .04 .01

.36***

9

–

(see Table 2 for factor loadings). Results from the CFA indicated good fit for five conceptually distinct factors that were labeled stimulation, sensitivity-responsivity, control-discipline, warmth, and EF-specific activities. The factors generally aligned with the four previously identified and theoretically-derived dimensions of parenting behaviors (e.g., control-discipline and sensitivityresponsivity; Landry & Smith, 2010), with the exception of scaffolding and a fifth factor of EF-specific activities (HEFE). In addition, an alternative one-factor model was identified and fit indices for the model suggested poor fit: 2 (135) = 423.71, p < .001, SRMR = .10, RMSEA = .13, CFI = .61, TLI = .55. A chi-squared difference test was conducted to compare the five-factor and one-factor nested model, showing a significant difference (2 (1) = 238.46, p < .001), suggesting that the five-factor structure is a better fit to the data. Finally, an alternative two-factor model, including EF-specific parenting practices and general parenting practices (e.g., praise), was identified and fit indices for the model indicated poor fit: 2 (134) = 347.50, p < .001, SRMR = .10, RMSEA = .12, CFI = .67, TLI = .62. A chi-squared difference test was conducted to compare the five-factor and two-factor nested models, showing a significant difference (2 (1) = 189.24, p < .001), suggesting that the five-factor structure is a better fit for the data. Overall, the CFA results suggest that the five-factor model was the best representation of the factor structure of the home environment data. 6.2. Is the HEFE factor predictive of children’s EF? 6.2.1. Model 1 To examine how parents’ use of EF-specific activities is associated with children’s performances on EF tasks, we conducted three hierarchical regressions for each measure of EF (i.e., card sorting task, HTKS, and Sun/Moon task). Results from Model 1 revealed a positive association between the EF-specific activities and the HTKS (ˇ = .23, p < .01, CI [1.44, 9.32]), but not the card sorting or Sun/Moon tasks (see Table 3).

Descriptive statistics Mean (SD) Range Skew Kurtosis

Notes. EF = executive function, HTKS = Head–Toes–Knees–Shoulders; HLE = home learning environment. * p < .05. ** p < .01. *** p < .001.

2.51 (.85) .33–4 −.02 −.31 3.25 (.65) 1–4 −.61 .14 5.88 (1.96) 1.51 (.50) 2.37 (.78) 2–9 0–1 .30–4.20 −.13 −.05 .03 −.93 −2.03 −.14 56.41 (6.29) 38–69 −.45 −.09

– .23* .48*** .51*** −0.13 .09 .08 – .47*** .44*** .68*** .84*** −.23* .07 .01

2 1 1. Age 2. Parent education 3. Gender 4. HLE 5. Stimulation 6. Sensitivity-responsivity 7. Control-discipline 8. Warmth 9. EF-specific activities 10. Card sorting task 11. HTKS 12. Sun/Moon

Table 2 Correlations and descriptive statistics for key study variables.

3

– −.22* −.04 −.14 −.01 −.02 −.04 −.19* −.15 −.12

– .39*** .29** .24** .11 .38*** .19* .34*** .22* – −.06 .12 −.10 −.12 −.13 −.27** −.12 .32*** .37** .27**

6 4

– .00 −.06 .06 −.25** −.10 −.04 −.10 −.20* .40*** .17 .29**

5

7

8

10

11

–

12

14

6.2.2. Model 2 To examine whether the EF-specific activities were related to children’s EF performances above and beyond the HLE and the general parenting factors, we conducted three additional hierarchical regressions for each direct assessment of EF. For the HTKS, Model 2 revealed a significant positive association for the parentreported EF-specific activities factor after controlling for the HLE and the general parenting factors (ˇ = .33, p = .04, CI [0.42, 15.09]). After controlling for child’s age, parent education, child’s gender, and all other HLE and parenting factors, higher scores on the HEFE factor were related to higher scores on the HTKS. Significant associations between the EF-specific activities factor and the card sorting and Sun/Moon tasks did not emerge (see Table 4). Additionally, only one of the general parenting factors (i.e., stimulation) significantly predicted one of the components of EF (i.e., the card sorting task), and the association was negative. None of the remaining parenting factors (i.e., sensitivity-responsivity, control-discipline, and warmth) predicted any of the measured EF outcomes (i.e., HTKS, Sun/Moon, card sorting task). Finally, the HLE was positively associated with all the EF outcomes. 7. Discussion This study examined the association between the home environment and children’s EF in a sample of families in the Midwestern region of the United States. In line with hypotheses, a conceptuallydistinct factor representing EF-specific activities in the home (i.e., the HEFE scale) emerged from a CFA along with four additional general parenting factors: stimulation, sensitivity-responsivity, control-discipline, and warmth. Just as direct numeracy and liter-

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

15

Table 3 Model 1 Associations between EF-specific activities in the home and EF. Card sorting task (n = 120)

Intercept Age Parent Education Gender EF-specific activities F Adjusted R2 Change in adjusted R2

HTKS (n = 120)

Sun/Moon (n = 113)

b

SE

ˇ

b

SE

ˇ

b

SE

ˇ

−9.44 0.38 1.05 −2.04 −0.37

5.49 0.08 0.27 1.04 0.72 11.18*** 0.28 0.00

– .37*** .31*** −.16 −.04

−26.55 0.59 3.42 −3.86 5.38

14.84 0.23 0.73 2.84 1.99 8.68*** 0.21 0.05**

– .22* .39** −.11 .23**

0.33 0.43 1.32 −1.31 0.67

8.90 0.13 0.39 1.50 1.03 5.58** 0.14 0.00

– .30** .30** −.08 .06

Notes. HTKS = Head–Toes–Knees–Shoulders; EF = executive function. * p < .05. ** p < .01. *** p < .001. Table 4 Model 2 Associations between EF-specific activities in the home and EF controlling for other home environment and parenting factors. Card sorting task (n = 120)

Intercept Age Parent education Gender HLE Stimulation Sensitivity-responsivity Control-discipline Warmth EF-specific activities F Adjusted R2 Change in adjusted R2

HTKS (n = 120)

Sun/Moon (n = 113)

b

SE

ˇ

b

SE

ˇ

b

SE

ˇ

−5.02 0.30 1.00 −1.89 2.29 −4.91 −0.83 0.43 3.10 1.81

5.59 0.09 0.28 1.04 1.05 1.99 0.75 1.42 2.76 1.35 6.23*** 0.28 0.01

– .29** .30*** −.15 .21* −.44* −.11 −.14 .14 .21

−17.89 0.42 3.32 −2.40 7.91 −9.90 −0.40 −1.55 10.25 7.75

15.03 0.23 0.75 2.88 2.89 5.46 2.07 3.91 7.59 3.70 4.97*** 0.23 0.03

– .15 .38*** −.07 .27* −.33 −.02 −.04 .18 .33*

−0.25 0.41 1.37 −0.39 3.16 −1.25 1.04 −1.78 5.16 −0.75

9.01 0.13 0.40 1.55 1.57 2.88 1.08 2.08 3.92 1.98 3.39** 0.16 0.00

– .29** .31** −.02 .21* −.09 .11 −.09 .18 −.07

Notes. HTKS = Head–Toes–Knees–Shoulders; EF = executive function, HLE = home learning environment. * p < .05. ** p < .01. *** p < .001.

acy practices in the home are related to children’s development of math and literacy skills (Anders et al., 2012; Farver, Xu, Lonigan, & Eppe, 2013), results suggested that the HEFE scale was significantly and positively related to a global assessment of children’s EF, the HTKS, above and beyond the HLE and other general parenting practices. No significant associations emerged between the HEFE scale and the card sorting or Sun/Moon tasks. This study provides empirical support that EF-specific activities comprise a separate and distinct factor of the home environment and that this factor is related to a measure of children’s global EF. Though these findings are correlational in nature, they provide a foundation for future research on the relations between the home environment and children’s EF skills. 7.1. HEFE scale as a distinct aspect of the home environment As expected, four of the five factors that emerged from the factor analysis generally mapped onto Landry and Smith’s (2010) dimensions of general parenting behaviors (with the exception of scaffolding), and one factor was comprised of the HEFE scale items, representing EF-specific activities in the home. These findings suggest that EF-specific activities in the home, as measured by the HEFE scale, are a distinct aspect of the home environment. The home learning environment has been found to be associated with several developmental domains, such as academic achievement (Melhuish et al., 2008). Further, domain-specific aspects of the home environment, such as the home numeracy and home literacy environments, have been identified and linked to children’s literacy, math, and language outcomes (Manolitsis et al., 2013; Schmitt et al., 2011).

However, no empirical work has explored the possibility of another domain-specific aspect of the home environment focused on EF. This is likely because to date, no measure of EF-specific activities had been developed. In this study, we identified items to include in the HEFE scale that may theoretically be related to children’s EF and that have been emphasized in previous research as being effective strategies for improving children’s EF in classroom settings, such as playing memory and concentration games (e.g., puzzles) and engaging in activities that require children to stop, think, then act (e.g., Red Light, Green Light; Davis et al., 2011; Duncan et al., 2017; Schmitt et al., 2015; Thorell et al., 2009; Winsler et al., 2011). Results indicated that the home EF environment is a unique component of the home learning environment and is distinct from general parenting practices such as being responsive and warm. Parents may be sensitive and responsive to their children’s needs but not engage their children in EF-specific activities in the home. Conversely, parents may participate in memory games or other activities that may promote EF but may not be characterized as generally warm or responsive. Given the importance of the development of EF in the early years, developing a scale that is comprised of parent-child activities in the home that are specific to EF is important and has implications for intervention development. The HEFE scale could be used in future research as a mechanism for identifying parent practices that may support children’s EF development. 7.2. Association between the HEFE scale and children’s EF An important finding that emerged from the present study is that the HEFE scale was predictive of children’s global EF skills,

16

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

as measured by the HTKS, even after controlling for demographic and child characteristics, as well as the HLE and general parenting practices. Children whose parents engaged more frequently in EF-specific activities in the home had higher scores on the HTKS. The home environment is the primary context where children initially learn to regulate their attention and emotions, and these skills have been argued to provide a foundation for the development of EF (Kopp, 1989; Zelazo et al., 2016). Thus, it is important to identify parenting practices that may be advantageous for the development of EF, and how frequently parents engage in these practices. The HEFE scale includes items that assess the frequency of parents playing memory games, games that require concentration and attention (e.g., puzzles), physical activity, and games that require children to stop, think, and then act (e.g., Simon Says). When practiced in the classroom environment, these activities have been shown to be effective in improving children’s EF (Davis et al., 2011; Schmitt et al., 2015; Thorell et al., 2009; Winsler et al., 2011). During these activities, children must focus their attention and concentrate, inhibit impulses, and in some cases, shift their attention to changing rules. Further, physical activity is often cognitively demanding, requiring children to concentrate, plan, and problem solve (Tomporowski et al., 2011). Thus, engaging in the activities included in the HEFE scale may allow children to practice and strengthen their global EF skills at home. Contrary to our hypotheses, there were no significant associations between the HEFE scale and the card sorting or Sun/Moon tasks. This could be due to differences across the three EF measures. The HTKS is a global measure of EF (McClelland & Cameron, 2012), assessing the integration of inhibitory control, cognitive flexibility, and working memory in children’s overt behavior. This is in contrast to the Sun/Moon task, which primarily taps inhibitory control, and the card sorting task, which primarily assesses cognitive flexibility. Many of the items on the HEFE scale reflect activities that target the integration of all three components of EF, which may explain why the HEFE scale predicts the HTKS but not the other more narrow assessments of EF. For example, one activity included in the HEFE is scale is the frequency with which parents play stop, think, act games with their child, such as Red Light, Green Light, a popular children’s game. In the traditional version of this game, a parent stands away from a child or group of children and acts as a traffic light. The parent then says red, yellow, or green which each corresponds to a different action (e.g., green means go) and the child or children try to reach the parent. This game requires children to integrate the three components of EF as children need to listen to and remember the rules of the games (i.e., “When I say green light, you walk; when I say red light, you stop;” working memory), switch from one rule to another (i.e., “Now when I say green light, you hop, and when I say red light, you stop; cognitive flexibility), and inhibit their impulse to just run right up to the parent (i.e., inhibitory control). As another example, engaging in puzzles requires the integration of the EF components. Children need to pay attention to the original object, remember the places of various pieces, and plan to successfully complete the activity. Also, unexpectedly, there were, in general, no significant associations between the four general parenting practices factors and children’s EF. Only one significant association emerged between stimulation and the card sorting task, but it was an unexpected negative association. This finding is not in line with previous literature suggesting a positive association between stimulation and children’s EF. These disparate findings may be due to measurement of the general parenting practices and EF in this study or sample characteristics. When the same model was tested without EF-specific activities being in the model, none of the general parenting practices were significantly related to children’s EF. This was surprising given that previous research has demonstrated a predictive link between similar measures of parenting practices included

in the current study and EF (Bernier et al., 2010; Blair et al., 2011; Landry et al., 2002; Lengua et al., 2007). One explanation for the non-significant links between general parenting practices and children’s EF may be a third, unmeasured variable. Previous studies examining the link between parenting practices (e.g., scaffolding) and children’s EF found that children’s verbal ability mediated the association between parenting and children’s EF (Hammond et al., 2012; Landry et al., 2002). In other words, in addition to its direct link, parental scaffolding was also indirectly related to children’s EF through their verbal abilities. Children’s verbal abilities are considered a critical skill for the development of other mental abilities such as EF (Clark et al., 2013; Hammond et al., 2012). Specifically, self-directed speech is argued to regulate children’s behavior by helping the behaviors to become more internalized, organized, and purposeful (Fernyhough & Fradley, 2005). Thus, children’s language ability may be a mechanism linking general parenting practices to children’s EF resulting in a non-significant direct association between these variables in this study. It is also important to note that researchers selectively include distinct components or various conceptualizations of parenting practices in their studies while examining their relation to children’s EF which limits the comparability between findings across studies. Different parenting practices factors may have distinct associations with EF depending on other factors included in statistical models. For example, when examining the association between multiple parenting practices and children’s regulatory abilities (e.g., effortful control), Lengua et al. (2007) found that scaffolding and limit setting were related to children’s EF but warmth and negative affect were not. Thus, the fact that four parenting factors were included in our models may have been why many of the non-significant relations with EF were found. Another important finding that emerged from the present study is that the HLE was predictive of children’s EF outcomes. Although this was not the primary focus of this study, findings highlight the importance of considering the HLE for children’s EF. This is in line with the extant literature documenting concurrent and longitudinal links between the quality of the HLE and children’s skills including language, literacy, and mathematics (Fantuzzo, McWayne, Perry, & Childs, 2004; Rodriguez & TamisLeMonda, 2011; Sénéchal & LeFevre, 2002; Son & Morrison, 2010; Votruba-Drzal, 2003). Findings also extend previous literature by emphasizing that when parents provide a stimulating and enriching environment that includes learning activities such as reading and counting together, they provide opportunities for children to develop their EF skills (e.g., paying attention, listening, following the directions). 7.3. Limitations and future directions Although the current study contributes to our understanding of aspects of the home environment that may be related to children’s EF, limitations must be noted. First, we used a convenience sample, which was fairly small and relatively homogenous in terms of ethnicity and parent education, thus limiting the generalizability of the findings. Future research should use random sampling and include larger, more ethnically diverse samples, with a more representative range of socioeconomic statuses. It must also be noted that one unexpected negative correlation emerged between general parenting practices (i.e., stimulation) and the card sorting task. This unexpected association may be due to the measurement of general parenting practices. Even though the general parenting practices items have been used and validated in previous research, future research should be aware that parenting items may not function in the expected directions across samples. An additional limitation is that the items collected in the HEFE scale were not exhaustive (i.e., only one item per activity was

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

included), and there are likely a number of additional parent-child activities or parental characteristics that contribute to children’s EF development. For example, parents may provide children with strategies for waiting patiently that may foster children’s EF skills. Future research will need to replicate the findings of the present study with the available items, as well as include additional EFspecific items. Another alternative mechanism linking EF-specific activities to children’s EF may be parental EF. Future research should consider measuring and controlling for parental EF when examining these associations. Although the internal consistency of the HEFE scale was good with the inclusion of all five items, results suggest it may be higher if the exercise item is deleted. The pattern of findings in this study is the same with and without the exercise item in the HEFE scale, however, future research should include more exercise items to evaluate its validity within the EF-specific items. Further, it could be that unmeasured parenting practices contribute to the development of EF. In this study, we measured four factors along with EF-specific activities. Other domain-specific activities in the home environment (e.g., home numeracy practices) or parental scaffolding may also be associated with EF. Finally, future research should use a more descriptive frequency scale (e.g., 0 = never, 1 = 1–3 times per month, 2 = about once per week, etc.) when measuring EF-specific activities. Though the scale that was currently used follows previous work, some options may be ambiguous and parents may interpret them differently (e.g., ‘always’). It must also be noted that the results of this study are correlational in nature and were collected at a single time point. As such, results cannot be interpreted in a causal framework. In addition, children with strong EF skills may initiate more EF-specific activities with parents. Future research should investigate the longitudinal and bidirectional relations between EF-specific activities and children’s EF skills, as well as the potential causal relations between activities and skills (e.g., through parenting interventions that promote EF activities in the home). Future research may benefit from utilizing an EF-specific home environment scale to both evaluate and implement EF bolstering practices. Further, researchers should continue to evaluate the context in which this scale is functional, and examine possible moderators (e.g., socioeconomic status). Finally, the HEFE scale is based on parent report. Due to reporter bias, self-report may provide less reliable information compared to an observational tool. Future research should validate the parent-report HEFE items using observational measures. 8. Conclusion Research suggests that EF is an important indicator of school readiness, and EF has also been positively associated with later math achievement, engagement in the classroom, better physical health, and personal finances, as well as negatively related to substance dependence and criminal charges (Best et al., 2011; Moffitt et al., 2011; Riggs et al., 2006). The purpose of the present study was to evaluate EF-specific activities, as measured by the HEFE scale, as a distinct aspect of the home environment and to explore the relation of the HEFE scale with children’s EF. Findings indicate that the HEFE scale is a distinct factor of the home environment and that it is related to children’s global EF. This study, therefore, is a foundational step for understanding the types of activities that may be supportive of children’s EF development. Future research can build on this study by exploring potential longitudinal and causal effects of EF-specific activities on children’s EF. Further, study findings may have implications for intervention work targeting families to promote EF in the home environment. The HEFE scale could be used in future research as a tool for measuring the frequency of EF-specific activities in the home environment and could inform future intervention research to improve children’s EF.

17

Declarations of interest None. References Anders, Y., Rossbach, H. G., Weinert, S., Ebert, S., Kuger, S., Lehrl, S., & von Maurice, J. (2012). Home and preschool learning environments and their relations to the development of early numeracy skills. Early Childhood Research Quarterly, 27, 231–244. http://dx.doi.org/10.1016/j.ecresq.2011.08.003 Archibald, S. J., & Kerns, K. A. (1999). Identification and description of new tests of executive functioning in children. Child Neuropsychology, 5, 115–129. http://dx. doi.org/10.1076/chin.5.2.115.3167 Bell, M. A., & Deater-Deckard, K. (2007). Biological systems and the development of self-regulation: Integrating behavior, genetics, and psychophysiology. Journal of Developmental & Behavioral Pediatrics, 28, 409–420. http://dx.doi.org/10. 1097/DBP.0b013e3181131fc7 Bernier, A., Carlson, S. M., Deschenes, M., & Matte-Gagne, C. (2012). Social factors in the development of early executive functioning: A closer look at the caregiving environment. Developmental Science, 15, 12–24. http://dx.doi.org/10.1111/j. 1467-7687.2011.01093.x Bernier, A., Carlson, S. M., & Whipple, N. (2010). From external regulation to self-regulation: Early parenting precursors of young children’s executive functioning. Child Development, 81, 326–339. http://dx.doi.org/10.1111/j.14678624.2009.01397.x Best, J. R. (2010). Effects of physical activity on children’s executive function: Contributions of experimental research on aerobic exercise. Developmental Review, 30, 331–351. http://dx.doi.org/10.1016/j.dr.2010.08.001 Best, J. R., Miller, P. H., & Naglieri, J. A. (2011). Relations between executive function and academic achievement from ages 5 to 17 in a large, representative national sample. Learning and Individual Differences, 21, 327–336. http://dx.doi. org/10.1016/j.lindif.2011.01.007 Bibok, M. B., Carpendale, J. I. M., & Muller, U. (2009). Parental scaffolding and the development of executive function. New Directions for Child and Adolescent Development, 123, 17–34. http://dx.doi.org/10.1002/cd.233 Bindman, S. W., Hindman, A. H., Bowles, R. P., & Morrison, F. J. (2013). The contributions of parental management language to executive function in preschool children. Early Childhood Research Quarterly, 28, 529–539. http://dx. doi.org/10.1016/j.ecresq.2013.03.003 Blair, C. (2002). School readiness: Integrating cognition and emotion in a neurobiological conceptualization of children’s functioning at school entry. American Psychologist, 57, 111–127. http://dx.doi.org/10.1037//0003-066X.57. 2.111 Blair, C., Protzko, J., & Ursache, A. (2011). Self-regulation and the development of early literacy. In D. Dickinson, & S. Neuman (Eds.), Handbook of early literacy research (Vol. 3) (pp. 20–35). New York: Guilford Press. Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Development, 78, 647–663. http://dx.doi.org/10.1111/j. 1467-8624.2007.01019.x Bradley, R. H., Burchinal, M. R., & Casey, P. H. (2001). Early intervention: The moderating role of the home environment. Applied Developmental Science, 5, 2–8. http://dx.doi.org/10.1207/S1532480XADS0501 1 Bradley, R. H., & Caldwell, B. M. (1995). Caregiving and the regulation of child growth and development: Describing proximal aspects of caregiving systems. Developmental Review, 15, 38–85. http://dx.doi.org/10.1006/drev.1995.1002 Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53, 371–399. http://dx.doi.org/10. 1146/annurev.psych.53.100901.135233 Caldwell, B. M., & Bradley, R. H. (1984). Home observation for measurement of the environment. In Little Rock. University of Arkansas Press. Campbell, D. W., Eaton, W. O., & McKeen, N. A. (2002). Motor activity level and behavioral control in young children. International Journal of Behavioral Development, 26, 289–296. http://dx.doi.org/10.1080/01650250143000166 Clark, C. A., Sheffield, T. D., Chevalier, N., Nelson, J. M., Wiebe, S. A., & Espy, K. A. (2013). Charting early trajectories of executive control with the shape school. Developmental Psychology, 49, 1481–1493. http://dx.doi.org/10.1037/a0030578 Davis, C. L., Tomporowski, P. D., McDowell, J. E., Austin, B. P., Miller, P. H., Yanasak, N. E., & Naglieri, J. A. (2011). Exercise improves executive function and achievement and alters brain activation in overweight children: A randomized controlled trial. Health Psychology, 30, 91–98. http://dx.doi.org/10.1037/ a0021766 Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–168. http://dx.doi.org/10.1146/annurev-psych-113011-143750 Duncan, R., Schmitt, S. A., & McClelland, M. M. (2017, April). Promoting school readiness by integrating a self-regulation intervention into a school-based summer program. In Paper presented at the biennial meeting for Society for Research in Child Development. Evans, M. A., Shaw, D., & Bell, M. (2000). Home literacy activities and their influence on early literacy skills. Canadian Journal of Experimental Psychology, 54, 65–75. Fantuzzo, J., McWayne, C. M., Perry, M. A., & Childs, S. (2004). Multiple dimensions of family involvement and their relations to behavioral and learning competencies for urban, low-income children. School Psychology Review, 33, 467–480.

18

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19

Farver, J. A. M., Xu, Y., Lonigan, C. J., & Eppe, S. (2013). The home literacy environment and Latino Head Start children’s emergent literacy skills. Developmental Psychology, 49, 775–791. http://dx.doi.org/10.1037/a0028766 Fay-Stammbach, T., Hawes, D. J., & Meredith, P. (2014). Parenting influences on executive function in early childhood: A review. Child Development Perspectives, 8, 258–264. http://dx.doi.org/10.1111/cdep.1209 Fernyhough, C., & Fradley, E. (2005). Private speech on an executive task: Relations with task difficulty and task performance. Cognitive Development, 20, 103–120. http://dx.doi.org/10.1016/j.cogdev.2004.11.002 Flook, L., Goldberg, S. B., Pinger, L., & Davidson, R. J. (2015). Promoting prosocial behavior and self-regulatory skills in preschool children through a mindfulness-based kindness curriculum. Developmental Psychology, 51, 44–51. http://dx.doi.org/10.1037/a0038256 Friedman, N. P., & Miyake, A. (2017). Unity and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex, 86, 186–204. http://dx.doi.org/10.1016/j.cortex.2016.04.023 Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P., & Hewitt, J. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137, 201–225. http://dx.doi.org/10.1037/0096-3445.137.2.201 Garon, N., Bryson, S. E., & Smith, I. M. (2008). Executive function in preschoolers: A review using an integrative framework. Psychological Bulletin, 134, 31–60. http://dx.doi.org/10.1037/0033-2909.134.1.31 Hammond, S. I., Müller, U., Carpendale, J. I., Bibok, M. B., & Liebermann-Finestone, D. P. (2012). The effects of parental scaffolding on preschoolers’ executive function. Developmental Psychology, 48, 271. http://dx.doi.org/10.1037/ a0025519 Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55. http://dx.doi.org/10. 1080/10705519909540118 Hughes, C., & Ensor, R. (2008). Does executive function matter for preschoolers’ problem behaviors? Journal of Abnormal Child Psychology, 36, 1–14. http://dx. doi.org/10.1007/s10802-007-9107-6 Hughes, C., Ensor, R., Wilson, A., & Graham, A. (2010). Tracking executive function across the transition to school: A latent variable approach. Developmental Neuropsychology, 35, 20–36. Kopp, C. B. (1989). Regulation of distress and negative emotions: A developmental view. Developmental Psychology, 25, 343–354. http://dx.doi.org/10.1037/00121649.25.3.343 Landry, S. H., Miller-Loncar, C. L., Smith, K. E., & Swank, P. R. (2002). The role of early parenting in children’s development of executive processes. Developmental Neuropsychology, 21, 15–41. http://dx.doi.org/10.1207/S15326942DN2101 2 Landry, S. H., & Smith, K. E. (2010). Early social and cognitive precursors and parental support for self-regulation and executive function: Relations from early childhood into adolescence. In B. W. Sokol, U. Müller, J. I. M. Carpendale, A. R. Young, & G. Iarocci (Eds.), Self and social regulation: Social interaction and the development of social understanding and executive functions (pp. 386–417). New York, NY: Oxford University Press. Lapointe, V. R., Ford, L., & Zumbo, B. D. (2007). Examining the relationship between neighborhood environment and school readiness for kindergarten children. Early Education and Development, 18, 473–495. http://dx.doi.org/10.1080/ 10409280701610846 LeFevre, J. A., Skwarchuk, S. L., Smith-Chant, B. L., Fast, L., Kamawar, D., & Bisanz, J. (2009). Home numeracy experiences and children’s math performance in the early school years. Canadian Journal of Behavioral Science, 41(2), 55. http://dx. doi.org/10.1037/a0014532 Lengua, L. J., Honorado, E., & Bush, N. R. (2007). Contextual risk and parenting as predictors of effortful control and social competence in preschool children. Journal of Applied Developmental Psychology, 28(1), 40–55. http://dx.doi.org/10. 1016/j.appdev.2006.10.001 Lerner, M. D., & Lonigan, C. J. (2014). Executive function among preschool children: Unitary versus distinct abilities. Journal of Psychopathology and Behavioral Assessment, 36, 626–639. Lewis, C., & Carpendale, J. I. (2009). Introduction: Links between social interaction and executive function. New Directions for Child and Adolescent Development, 2009(123), 1–15. http://dx.doi.org/10.1002/cd.232 Lonigan, C. J., Lerner, M. D., Goodrich, M. J., Farrington, A. L., & Allan, D. M. (2016). Executive function of Spanish-speaking language-minority preschoolers: Structure and relations with early literacy skills and behavioral outcomes. Journal of Experimental Psychology, 144, 46–65. Lovejoy, M. C., Weis, R., O’Hare, E., & Rubin, E. C. (1999). Development and initial validation of the Parent Behavior Inventory. Psychological Assessment, 11, 534–545. http://dx.doi.org/10.1037/1040-3590.11.4.534 Manolitsis, G., Georgiou, G. K., & Tziraki, N. (2013). Examining the effects of home literacy and numeracy environment on early reading and math acquisition. Early Childhood Research Quarterly, 28, 692–703. http://dx.doi.org/10.1016/j. ecresq.2013.05.004 McClelland, M. M., & Cameron, C. (2012). Self-regulation in early childhood: Improving conceptual clarity and developing ecologically-valid measures. Child Development Perspectives, 6, 136–142. http://dx.doi.org/10.1111/j.17508606.2011.00191.x McClelland, M. M., Acock, A. C., Piccinin, A., Rhea, S. A., & Stallings, M. C. (2013). Relations between preschool attention span-persistence and age 25 educational outcomes. Early Childhood Research Quarterly, 28, 314–324. http:// dx.doi.org/10.1016/j.ecresq.2012.07.008

McClelland, M. M., Cameron, C. E., Duncan, R., Bowles, R. P., Acock, A. C., Miao, A., & Pratt, M. E. (2014). Predictors of early growth in academic achievement: The Head–Toes–Knees–Shoulders task. Frontiers in Psychology, 5, 1–14. http://dx. doi.org/10.3389/fpsyg.2014.00599 McClelland, M. M., Connor, C. M., Jewkes, A. M., Cameron, C. E., Farris, C. L., & Morrison, F. J. (2007). Links between behavioral regulation and preschoolers’ literacy, vocabulary, and math skills. Developmental Psychology, 43, 947–959. http://dx.doi.org/10.1037/0012-1649.43.4.947 McClelland, M. M., Geldhof, J., Morrison, F., Gestsdottir, S., Cameron, C., Bowers, E., . . . & Grammer, J. (2018). Self-Regulation. In N. Halfon, C. Forrest, R. Lerner, & E. Faustman (Eds.), Handbook of life course health development. Springer Cham. http://dx.doi.org/10.1007/978-3-319-47143-3 12 Melhuish, E. C., Phan, M. B., Sylva, K., Sammons, P., Siraj-Blatchford, I., & Taggart, B. (2008). Effects of the home learning environment and preschool center experience upon literacy and numeracy development in early primary school. Journal of Social Issues, 64, 95–114. http://dx.doi.org/10.1111/j.1540-4560. 2008.00550.x Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., & Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences of the United States of America, 108, 2693–2698. http://dx.doi.org/10.1073/pnas.1010076108 National Institute of Child Health and Human Development. (2005). Predicting individual differences in attention, memory, and planning in first graders from experiences at home, child care, and school. Developmental Psychology, 41, 99–114. http://dx.doi.org/10.1037/0012-1649.41.1.99 Raver, C. C., Jones, S. M., Li-Grining, C., Zhai, F., Bub, K., & Pressler, E. (2011). CSRP’s impact on low-income preschoolers’ preacademic skills: Self-regulation as a mediating mechanism. Child Development, 82, 362–378. http://dx.doi.org/10. 1111/j.1467-8624.2010.01561.x Razza, R. A., & Blair, C. (2009). Associations among false-belief understanding, executive function, and social competence: A longitudinal analysis. Journal of Applied Developmental Psychology, 30(3), 332–343. http://dx.doi.org/10.1016/j. appdev.2008.12.020 Revelle, W. (2016). Procedures for personality and psychological research. Evanston, IL, USA: Northwestern University [Version=1.6.12]. https://CRAN.R-project. org/package=psych Riggs, N. R., Jahromi, L. B., Razza, R. P., Dillworth-Bart, J. E., & Mueller, U. (2006). Executive function and the promotion of social–emotional competence. Journal of Applied Developmental Psychology, 27, 300–309. http://dx.doi.org/10.1016/j. appdev.2006.04.002 Robinson, C. C., Mandleco, B., Olsen, S. F., & Hart, C. H. (1995). Authoritative, authoritarian, and permissive parenting practices: Development of a new measure. Psychological Reports, 77, 819–830. http://dx.doi.org/10.2466/pr0. 1995.77.3.819 Robinson, C. C., Hart, C. H., Madleco, B. L., Olsen, S. F., Russell, A., Aloa, V., & Bazarskaya, N. (1996). Psychometric support for a new measure of authoritative, authoritarian, and permissive parenting practices: Cross-cultural connections. In Paper presented at the Biennial International Society for the Study of Behavrioal Development Conference. Rodriguez, E. T., & Tamis-LeMonda, C. S. (2011). Trajectories of the home learning environment across the first 5 years: Associations with children’s vocabulary and literacy skills at prekindergarten. Child Development, 82, 1058–1075. http://dx.doi.org/10.1111/j. 1467–8624.2011.01614.x Rueda, M. R., Rothbart, M. K., McCandliss, B. D., Saccomanno, L., & Posner, M. I. (2005). Training, maturation, and genetic influences on the development of executive attention. Proceedings of the National Academy of Sciences, 102(41), 14931–14936. Sénéchal, M., & LeFevre, J.-A. (2002). Parental involvement in the development of children’s reading skill: A five-year longitudinal study. Child Development, 73, 445–460. http://dx.doi.org/10.1111/1467-8624.00417 Sameroff, A. (2010). A unified theory of development: A dialectic integration of nature and nurture. Child Development, 81, 6–22. http://dx.doi.org/10.1111/j. 1467-8624.2009.01378.x Schmitt, S. A., Korucu, I., Jones, B. L., Snyder, F. J., Evich, C. D., & Purpura, D. J. (2017). Self-regulation as a correlate of weight status in preschool children. Early Child Development and Care, 1–11. http://dx.doi.org/10.1080/03004430.2017. 1299715 Schmitt, S. A., McClelland, M. M., Tominey, S. L., & Acock, A. C. (2015). Strengthening school readiness for Head Start children: Evaluation of a self-regulation intervention. Early Childhood Research Quarterly, 30, 20–31. http://dx.doi.org/10.1016/j.ecresq.2014.08.001 Schmitt, S. A., Simpson, A. M., & Friend, M. (2011). A longitudinal assessment of the home literacy environment and early language. Infant and Child Development, 20, 409–431. http://dx.doi.org/10.1002/icd.733 Sektnan, M., McClelland, M. M., Acock, A., & Morrison, F. J. (2010). Relations between early family risk, children’s behavioral regulation, and academic achievement. Early Childhood Research Quarterly, 25, 464–479. http://dx.doi. org/10.1016/j.ecresq.2010.02.005 Son, S. H., & Morrison, F. J. (2010). The nature and impact of changes in home learning environment on development of language and academic skills in preschool children. Developmental Psychology, 46, 1103–1118. http://dx.doi. org/10.1037/a0020065 Thorell, L. B., Lindqvist, S., Nutley, S. B., Bohlin, G., & Klingberg, T. (2009). Training and transfer effects of executive functions in preschool children. Developmental Science, 12, 106–113. http://dx.doi.org/10.1111/j.1467-7687.2008.00745.x

I. Korucu et al. / Early Childhood Research Quarterly 47 (2019) 9–19 Tominey, S. L., & McClelland, M. M. (2011). Red light, purple light: Findings from a randomized trial using circle time games to improve behavioral self-regulation in preschool. Early Education & Development, 22, 489–519. http://dx.doi.org/10. 1080/10409289.2011.574258 Tomporowski, P. D., Lambourne, K., & Okumura, M. S. (2011). Physical activity interventions and children’s mental function: An introduction and overview. Preventive Medicine, 52, S3–S9. http://dx.doi.org/10.1016/j.ypmed.2011.01.028 Ursache, A., Blair, C., & Raver, C. C. (2012). The promotion of self-regulation as a means of enhancing school readiness and early achievement in children at risk for school failure. Child Development Perspectives, 6, 122–128. http://dx.doi.org/ 10.1111/j.1750-8606.2011.00209 Votruba-Drzal, E. (2003). Income changes and cognitive stimulation in young children’s home learning environments. Journal of Marriage and Family, 65, 341–355. Wanless, S. B., McClelland Acock, A. C., Chen, F.-M., & Chen, J.-L. (2011). Behavioral regulation and early academic achievement in Taiwan. Early Education and Development, 22, 1–28. http://dx.doi.org/10.1080/10409280903493306 Wanless, S. B., McClelland, M. M., Tominey, S. L., & Acock, A. C. (2011). The influence of demographic risk factors on children’s behavioral regulation in

19

prekindergarten and kindergarten. Early Education & Development, 22, 461–488. http://dx.doi.org/10.1080/10409289.2011.536132 Winsler, A., Ducenne, L., & Koury, A. (2011). Singing one’s way to self-regulation: The role of early music and movement curricula and private speech. Early Education and Development, 22, 274–304. http://dx.doi.org/10.1080/ 10409280903585739 Zelazo, P. D. (2006). The dimensional change card sort (DCCS): A method of assessing executive function in children. Nature Protocols, 1, 297–301. http:// dx.doi.org/10.1038/nprot.2006.46 Zelazo, P. D., Craik, F. I. M., & Booth, L. (2004). Executive function across the life span. Acta Psychologica, 115, 167–183. http://dx.doi.org/10.1016/j.actpsy.2003. 12.005 Zelazo, P. D., Blair, C. B., & Willoughby, M. T. (2016). Executive function: Implications for education (NCER 2017-2016). Washington, DC: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education. Zelazo, P. D., & Muller, U. (2011). Executive function in typical and atypical development. In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development (2nd ed., Vol. 3, pp. 574–603). Hoboken, NJ: Wiley-Blackwell.