Validation of the Head–Toes–Knees–Shoulders task in Native Hawaiian and non-Hawaiian children

Early Childhood Research Quarterly 44 (2018) 192–205

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Early Childhood Research Quarterly

Validation of the Head–Toes–Knees–Shoulders task in Native Hawaiian and non-Hawaiian children夽 Puanani J. Hee ∗ , Yiyuan Xu, Alexander Krieg ¯ Department of Psychology, University of Hawai‘i at Manoa, United States

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Article history: Received 15 June 2016 Received in revised form 3 November 2017 Accepted 28 December 2017 Keywords: Head–Toes–Knees–Shoulders task (HTKS) Behavioral self-regulation Native Hawaiian

a b s t r a c t The current study examined psychometric properties, as well as convergent, discriminant, and predictive validity of the Head–Toes–Knees–Shoulders (HTKS) task with a sample of Native Hawaiian and nonHawaiian kindergartners from a rural community in Hawai‘i. There were 120 (58 girls, 62 boys; 71 Native Hawaiian, 49 non-Hawaiian) participants (M = 59.79 months; SD = 5.00). Children completed the 20-item version of the HTKS task in the fall (T1) and spring (T2) semester of kindergarten. The criterion measures for convergent validity included the Peg Tapping Task (PTT), and parent and teacher measures of attention, working memory, and inhibitory control that assessed “cool” aspects of self-regulation, whereas the criterion measures for discriminant validity included parent and teacher measures of emotional control and impulsivity that tapped “hot” aspects of self-regulation. The Test of Preschool Early Literacy (TOPEL) was used as the criterion measure for predictive validity. The results supported the one-factor model of the HTKS. The HTKS items also had satisfactory item properties based on item characteristic curves and most items did not show differential item functions (DIFs) between Native Hawaiian and non-Hawaiian children. In addition, the two-factor model of “cool” and “hot” self-regulation fit the data satisfactorily at T1 but not T2, providing modest evidence for convergent and discriminant validity. With regard to predictive validity, path analyses showed that the HTKS scores at T1 were positively associated with the TOPEL scores at T1, but not at T2 (after controlling for the TOPEL scores at T1). We discuss the importance of developing the self-regulation skills of Native Hawaiian children from at-risk backgrounds as they enter formal schooling. © 2018 Elsevier Inc. All rights reserved.

Self-regulation has been established as one of the most important school readiness skills for children entering kindergarten (Blair, 2002; Duncan et al., 2007; McClelland, Acock, & Morrison, 2006). Self-regulation is associated with children’s early literacy, math, and language skills (Blair & Razza, 2007; McClelland, Cameron, Connor, Farris, Jewkes, & Morrison, 2007), classroom behavior (Cameron Ponitz, McClelland, Matthews, & Morrison, 2009), and later academic success (McClelland et al., 2006; McClelland, Acock, Piccinin, Rhea, & Stallings, 2013). Despite substantial research supporting the relation between self-regulation

夽 This research was supported in part by a fellowship awarded to Puanani J. Hee by the American Psychological Association Minority Fellowship Program Mental Health and Substance Abuse Services [SM060563], and by a Hawai‘i Research Initiative Grant awarded to Yiyuan Xu by the Social Science Research Institute, University of ¯ Hawai‘i at Manoa. ∗ Corresponding author at: Department of Psychology, University of Hawai‘i at ¯ 2530 Dole Street, Sakamaki C 400, Honolulu, HI 96822-2294, United States. Manoa, E-mail address: [email protected] (P.J. Hee). https://doi.org/10.1016/j.ecresq.2017.12.007 0885-2006/© 2018 Elsevier Inc. All rights reserved.

and children’s short- and long-term developmental outcomes, there are still a limited number of age-appropriate assessments of self-regulation in young children that do not rely on parents’ or teachers’ perception. The Head–Toes–Knees–Shoulders task (HTKS; Cameron Ponitz et al., 2009) was recently developed to address this concern, and has shown remarkable reliability and validity for young children of diverse ethnic (Cameron Ponitz et al., 2008; Cameron Ponitz et al., 2009; Caughy, Mills, Owen, & Hurst, 2013; Connor et al., 2010; Fuhs, Farran, & Nesbitt, 2015; Graziano et al., 2015; Nesbitt, Farran, & Fuhs, 2015) and cultural backgrounds (Gestsdottir et al., 2014; Lan, Legare, Cameron Ponitz, Li, & Morrison, 2011; Son, Lee, & Sung, 2013; Wanless, McClelland, Acock et al., 2011; Wanless et al., 2013). The purpose of the current study was to extend validation of the HTKS to a sample of Native Hawaiian and non-Hawaiian children from a rural community in Hawai‘i.

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1. Self-regulation among young children Self-regulation represents a multidimensional construct that involves cognitive, behavioral, and physiological components, and enables individuals to maintain an optimal level of emotional, motivational, and cognitive arousal to adaptively modulate their behavior (Blair & Raver, 2012; McClelland, Cameron Ponitz, Messersmith, & Tominey, 2010; Vohs & Baumeister, 2011). The term self-regulation has been used to refer to both top-down planning processes and bottom-up regulation of more reactive impulses (Blair & Raver, 2012; Zelazo & Cunningham, 2007), and is sometimes used interchangeably with other related terms, such as effortful control (EC) in personality and temperament literature (Eisenberg, Valiente, & Eggum, 2010; Liew, 2012; Rothbart & Bates, 2006; Zhou, Chen, & Main, 2012), or executive function (EF) by some researchers who use cognitive and neural system approaches (Blair, Zelazo, & Greenberg, 2005; Blair & Raver, 2012). In an attempt to link these research domains, Zelazo and Carlson (2012) differentiated “hot” from “cool” aspects of EF based on the degree of motivational and emotional salience of the situation; the “hot” EF occurs in situations that are affectively and emotionally salient, such as having control over one’s emotions, whereas the “cool” EF occurs in situations that are more affectively neutral and thus focus on cognitive aspects such as working memory, inhibitory control and focused attention/shifting. Although the conceptual distinction between “hot” and “cool” EF is clear (Zelazo & Carlson, 2012), there is mixed evidence in behavioral research distinguishing these two types of EFs, particularly among young children (e.g., Allan & Lonigan, 2011, 2014). The current study focused on behavioral self-regulation related to “cool” aspects of EF that involve directing, planning, and controlling attention, cognition, and behavior (Baumeister & Vohs, 2004; Cameron Ponitz et al., 2008), and that are often manifested in adaptive behavior within learning contexts (Cameron Ponitz et al., 2009; McClelland & Cameron, 2012). Specifically, we focused on three self-regulatory abilities, attention focusing/shifting, working memory, and inhibitory control that are particularly noteworthy in relation to young children’s transition to formal schooling (Cameron Ponitz et al., 2008; McClelland et al., 2007). Attention focusing/shifting refers to the ability to simultaneously focus on a task, ignore other distractions, and flexibly shift attention to new tasks when needed (Barkley, 1997; Rothbart & Posner, 2005; Rueda, Posner, & Rothbart, 2005). Attention focusing/shifting allows children to focus on a class activity amidst distractions and transition to new classroom tasks. Working memory helps children hold and process information while absorbing new material (Gathercole & Pickering, 2000; Kail, 2003), such as recalling classroom rules while engaging in an activity. Inhibitory control allows children to hinder an initial response in favor of one that is more adaptive such as raising one’s hand instead of shouting out (Dowsett & Livesey, 2000). By integrating attention focusing/shifting, working memory, and inhibitory control, young children can regulate their behavior, recall instructions, and focus on and complete tasks. Substantial research indicates attention focusing/shifting, working memory, and inhibitory control, measured independently from one another and together, predicts school success in early childhood and beyond (Blair & Razza, 2007; Cameron Ponitz et al., 2009; Duncan et al., 2007; McClelland et al., 2007). Stronger behavioral self-regulation is related to better math and literacy achievement in preschool (Allan & Lonigan, 2011; Blair & Razza, 2007; McClelland et al., 2007) and kindergarten (Cameron Ponitz et al., 2009; Matthews, Cameron Ponitz, & Morrison, 2009; McClelland et al., 2014). The three self-regulation skills tapped by the HTKS may be particularly important for developing early literacy skills among young children. To grow their oral language and print knowledge and improve their phonological awareness

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(i.e., three important components of early literacy skills; Lonigan, Schatschneider, & Westberg, 2008), children need to attend to instructions and academic material, to complete a task while keeping a set of rules in mind, and self-correct. These self-regulation skills, which can be assessed by the HTKS, are assumed to play key roles both in children’s ability to take advantage of instruction and in their ability to control their behavior in the classroom in adaptive and productive ways. Behavioral self-regulation has also been identified as a protective factor for youth with demographic risk such as ethnic minority status and poverty (Evans & Rosenbaum, 2008; Sektnan, McClelland, Acock, & Morrison, 2010). For instance, in a sample of 134 low-income and Spanish English Language Learner preschoolers, McClelland and Wanless (2012) found children’s higher self-regulation in the fall to be related to better academic achievement that year and during the transition to kindergarten. Similarly, in a sample of 100 preschoolers (55% minority, 51% enrolled in Head Start), Duncan, McClelland, and Acock (2017), found children’s behavioral self-regulation skills to be related to their academic achievement, regardless of family income. 2. Measures of behavioral self-regulation in young children Early assessments of self-regulation often relied on parent, teacher, or caregiver ratings, which may be susceptible to perception bias (McClelland & Cameron, 2012). These studies typically conceptualized self-regulation as part of a broader learning skills domain (e.g., Cooper & Farran, 1991), and its assessment was dependent on the context (e.g., home or school) where the child is observed (Smith-Donald, Raver, Hayes, & Richardson, 2007). Although some behavioral measures had been developed for clinical populations or for administration in a laboratory setting (Blair et al., 2005; Smith-Donald et al., 2007), they were typically lengthy, and required specialized materials and expert training (McClelland & Cameron, 2012; Schmitt, Pratt, & McClelland, 2014). Many measures of self-regulation are not appropriate for use with young children, and the existing ones, such as delayed gratification and Stroop tasks, focus primarily on inhibitory control (e.g., Gerstadt, Hong, & Diamond, 1994; Kochanska, Murray, Jacques, Koenig, & Vandegeest, 1996; Mischel, Shoda, & Rodriguez, 1989). For instance, Diamond and Taylor (1996) developed a simple Peg Tapping Task (PTT; also known as the Pencil Tapping Task) in which children are asked to tap a peg once when the examiner taps twice, and tap twice when the examiner taps once. However, tasks such as the PTT primarily focus on young children’s inhibitory control and do not examine other important aspects of self-regulation such as attention shifting. This is at odds with the notion that young children often integrate multiple aspects of self-regulation skills such as attention, working memory, and inhibitory control to solve problems (Wiebe, Epsy, & Charak, 2008; Zhou et al., 2012). The Head–Toes–Knees–Shoulders (HTKS) task was developed as an integrative measure of behavioral self-regulation (McClelland & Cameron, 2012) that is particularly easy to use because it does not place a demand on coordination of fine motor skills that may not be fully developed for many young children (Cameron Ponitz et al., 2008). 3. The Head–Toes–Knees–Shoulders (HTKS) task The HTKS task is a brief game designed to be used with children ages four to six that does not require lengthy training or specialized material. Instead, this task relies on four paired behavioral commands presented by the examiner to the child: “touch your head,” “touch your toes,” “touch your shoulders,” and “touch your knees.” Children are first asked to respond naturally to the command and

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then are directed to do the opposite of what is stated (e.g., touch their knees when instructed to “touch your shoulders”). This task requires multiple aspects of behavioral self-regulation as it directs children to pay attention to the instruction, use working memory to recall the multiple task rules while executing a response, and use inhibitory control to refrain from an initial response while displaying an unnatural, correct response (Cameron Ponitz et al., 2009; McClelland and Cameron, 2012, McClelland et al., 2014; Wanless, McClelland, Acock et al., 2011). The HTKS has demonstrated strong evidence for both reliability and validity. Test–retest reliability has been demonstrated with correlations above .70 in kindergarten children (McClelland et al., 2014; Wanless, McClelland, Tominey, & Acock, 2011). Prior research has also indicated a strong inter-rater reliability (Cohen’s kappa >.90; Cameron Ponitz et al., 2009) with weighted Cohen’s kappas above .79 (Becker, Miao, Duncan, & McClelland, 2014; McClelland et al., 2014). Evidence for convergent validity include significant associations between the HTKS scores and parents’ ratings on standardized measures of attention focusing and inhibitory control (Cameron Ponitz et al., 2009), other assessments of specific components of behavioral self-regulation that are tapped by the HTKS, such as cognitive flexibility, and working memory (Graziano et al., 2015; McClelland et al., 2014), and teacher-rated classroom self-regulation (Cameron Ponitz et al., 2009; Fuhs et al., 2015; Schmitt et al., 2014). In addition, the HTKS has shown evidence of predictive validity, including its positive relations to early math, literacy, and vocabulary achievement outcomes (Matthews et al., 2009; McClelland et al., 2007; McClelland et al., 2014; Wanless, McClelland, Acock et al., 2011; von Suchodoletz et al., 2013). The HTKS has also shown promising psychometric properties across diverse ethnic and cultural groups. For instance relations between the HTKS and children’s early academic skills have been demonstrated in Caucasian, African American, Latino, and Asian monoracial and biracial children in North America (Cameron Ponitz et al., 2009; Connor et al., 2010; Duncan et al., 2017; Graziano et al., 2015; McClelland & Wanless, 2012; Nesbitt et al., 2015; Schmitt et al., 2014; Wanless, McClelland, Tominey et al., 2011), French, German, and Icelandic children (Gestsdottir et al., 2014; von Suchodoletz et al., 2013), Chinese, South Korean, and Taiwanese children (Lan et al., 2011; Son et al., 2013; Wanless, McClelland, Acock et al., 2011; Wanless et al., 2013), and with children in Portugal (Cadima, Gamelas, McClelland, & Peixoto, 2015). The HTKS has also been correlated with teacher ratings of self-regulation and classroom behavior in children with low socioeconomic status and rural backgrounds (Cameron Ponitz et al., 2009; Duncan et al., 2017; Fuhs, Nesbitt, Farran, & Dong, 2014; Fuhs et al., 2015; Wanless, McClelland, Tominey et al., 2011). Despite this progress, few studies have investigated the reliability and validity of the HTKS with children from rural indigenous cultural communities or examined whether the HTKS items function similarly or differently across different ethnic groups. The HTKS has a particular advantage with rural Native Hawaiian children because it requires limited verbal command and is “user-friendly,” given its integration with the well-known children’s song Head, Shoulders, Knees and Toes that is familiar to rural Native Hawaiian and non-Hawaiian children. Given the importance of behavioral self-regulation for children’s early academic success (Blair & Razza, 2007; Fuhs et al., 2014; McClelland et al., 2007), and the potential role it might play in reducing ethnic and urban-rural disparities in early achievement, particularly among indigenous populations (Caughy et al., 2013; Murry & Brody, 1999; Rimm-Kaufman, Pianta, & Cox, 2000), the main purpose of the current study was to examine the validity of the HTKS in a sample of primarily low-income part-Native Hawaiian and multi-ethnic children from a rural community in Hawai‘i, a group at significant

risk for academic failure (Kamehameha Schools, 2014; Marsella, Oliveira, Plummer, & Crabbe, 1998).

4. The rural community in Hawai‘i The participants attended two elementary schools located in a rural community in Hawai‘i. This school complex has a high concentration of multiethnic children with a significant number of them having Native Hawaiian heritage; one school had 31.5% Native Hawaiian students and the other had 51.9% (Hawai‘i State Department of Education, 2014). Native Hawaiians are the indigenous people of Hawai‘i and are similar to American Indians and Alaska Natives in that they are descendants of the original inhabitants of territories currently under U.S. control (Kaholokula et al., 2012). Significant disparities in economic, social, and health status exist between Native Hawaiians and other ethnic groups in Hawai‘i. Native Hawaiians are more likely to be undereducated, have poor living conditions, and have low paying jobs (Office of Hawaiian Affairs, 2006). According to the U.S. Census Bureau 2010–2012 American Community Survey, an estimated 17.4% of Native Hawaiians in Hawai‘i live in poverty (in comparison to 11.5% of the total population), and approximately 23.3% of Native Hawaiian children under 5 years old live in poverty (U.S. Census Bureau, 2012). Less than 50% of Native Hawaiians achieve a high school diploma or equivalent (Marsella et al., 1998), and less than 50% of kindergarten children in the state demonstrate key skills and characteristics deemed necessary for a successful learning experience in school (Hawai‘i State Department of Education, 2012). While indigenous rural populations have been of increasing interest to early education researchers, there is a paucity of data on Native Hawaiian children and families. First, despite their unique historical and cultural backgrounds, Native Hawaiians are often collapsed with other Asian and Pacific Islander groups under the category “American Asian and Pacific Islander (AAPI),” which likely results in an inaccurate portrayal of the educational performance and challenges faced by Native Hawaiian children. Second, historically, Native Hawaiians were once the most literate ethnic group in Hawai‘i and in the late 1800s the literacy rates of Native Hawaiians exceeded much of the world (Lind, 1980; Nogelmeier, 2010; Wurdeman-Thurston & Kaomea, 2015). However, decades of American colonialization and segregation, and the systematic ban of the native language in schools, have had detrimental consequences on the early learning and language development among Native Hawaiian children, calling for efforts to identify factors that may be particularly instrumental in fostering school success for this cultural group (Wilson & Kawai‘ae‘a, 2007; Wurdeman-Thurston & Kaomea, 2015). These efforts would obviously include the development and/or validation of measures of protective factors that are suitable for young children as they transition to formal schooling. Thus, it was important to evaluate the validity of behavioral measures such as the HTKS with Native Hawaiian children, which can help capture early developing self-regulation, a known protective factor of school success for many minority groups. The rural community where the present sample was drawn from was characterized by many disadvantaged homes. According to the Hawai‘i State Department of Education School Status and Improvement Report (2014), the percentage of students receiving free or reduced-cost lunch during the study year was 67.2% and 54.1%, respectively, and both schools receive Title 1 funding due to community poverty levels (Hawai‘i State Department of Education, 2012). Additionally, only slightly more than half (64% and 59%) of the incoming kindergartners in each school had some preschool experience (Hawai‘i State Department of Education, 2012). This is consistent with data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (ECLS-K: 2011) which showed

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Fig. 1. Convergent and discriminant validity of the HTKS at T1. T = teacher rating, P = parent rating. HTKS = Head–Toes–Knees–Shoulders task; PTT = Peg Tapping Task; CBQ = Child Behavior Questionnaire (At = attention focusing, Inh = inhibitory control, Im = impulsivity-reverse coded); CTRS = Conners’ Teacher Rating Scale (Ina = inattention-reverse coded); BRIEF = Behavior Rating Inventory of Executive Function (Wm = working memory problems-reverse coded, Ec = emotion control problems-reverse coded). *p < .05, ** p < .01.

that it was less common for Native Hawaiian and Pacific Island children, as a combined group, to attend a center-based setting as the primary early childhood education arrangement during the year prior to kindergarten, than children of other ethnic/racial groups, including other minority groups (Rathbun & Zhang, 2016).

5. The current study The current study had four objectives. First, we examined psychometric properties of the HTKS at two time points: first when children entered kindergarten (Time 1: T1), and then during the spring semester of kindergarten (Time 2: T2), including its internal consistency, factor structure, test-retest reliability, item characteristic curves, and differential item functions. Second, to highlight the at-risk status of Native Hawaiian children, we compared the HTKS scores, and performance on a standardized early literacy measure, the Test of Preschool Early Literacy (TOPEL; Lonigan, Wagner,

Torgesen, & Rashotte, 2007), between Native Hawaiian and nonHawaiian children in the current sample, and between Native Hawaiian children and children of other cultural backgrounds, drawing data from publicly available databases and publications. Third, we investigated the convergent and discriminant validity of the HTKS using confirmatory factor analyses, in which its relations with a range of other behavioral, parent, and teacher measures of self-regulation were examined (see Figs. 1 and 2). Specifically, to examine convergent validity, we included parent and teacher measures that were designed to assess one or more “cool” aspects of self-regulation captured by the HTKS: attention (or lack thereof), (lack of) working memory, and inhibitory control, as well as the PTT, which primarily assesses inhibitory control. To address discriminant validity, we included parent and teacher measures that were designed to assess “hot” aspects of self-regulation that are not captured by the HTKS, such as emotional control and impulsivity. Finally, using path analyses, we examined the predictive validity

Fig. 2. Convergent and discriminant validity of the HTKS at T2. T = Teacher rating, HTKS = Head–Toes–Knees–Shoulders task; CBQ = Child Behavior Questionnaire (At = attention focusing, Inh = inhibitory control, Im = impulsivity-reverse coded); CTRS = Conners’ Teacher Rating Scale (Ina = inattention-reverse coded). *p < .05, ** p < .01.

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Fig. 3. Predictive validity of the HTKS. HTKS = Head–Toes–Knees–Shoulders task; TOPEL = Test of Preschool Early Literacy.

of the HTKS in relation to the TOPEL scores both concurrently and prospectively (see Fig. 3). 6. Method 6.1. Participants The participants were 120 (58 girls, 62 boys) children aged 52–77 months (M = 59.79; SD = 5.00). The sample was recruited from incoming kindergarten cohorts at two elementary schools in a rural community in Hawai‘i. There were four kindergarten classrooms at each school with one main teacher for each classroom. All children attending kindergarten in each participating school were eligible for inclusion in the study unless the child had been retained and was attending kindergarten for the second time. One child was excluded from the study due to behavioral difficulties during testing. Approximately 75% of the incoming kindergarten cohort from each school participated in this study. Due to a long history of common inter-ethnic marriage, the participating children were mostly multi-ethnic (n = 92; 76.67%), a demographic characteristic that is unique yet representative of communities in Hawai‘i. The twenty-eight mono-ethnic children included fifteen Filipinos, three Native Hawaiians, and ten children of White, Black, Marshallese, and Hispanic backgrounds. Due to the small number of mono-ethnic children and our primary interest in children of Native Hawaiian heritage that are at particularly high risk for early academic struggle, children’s ethnic backgrounds were coded as Native Hawaiian (including both mono- and multiethnic, n = 71) or non-Hawaiian (n = 49).1 6.2. Procedure This study was part of a larger study that aimed to understand and examine the early transition to formal schooling among Native

1 Native Hawaiians are descendants of the original people of Hawai‘i (Office of Hawaiian Affairs, 2006). The Native Hawaiian population declined significantly following Western contact and colonization in the 19th and 20th centuries, and since then, many have intermarried, which has resulted in the majority of Native Hawaiians being multiethnic or multiracial (Marsella et al., 1998; McCubbin & Marsalla, 2009).

*p < .05, ** p < .01.

Hawaiian and non-Hawaiian children. Children were recruited during kindergarten orientation meetings and during the first week of school, at which time researchers introduced the study to parents and obtained their written consent. Parents were told that their participation would contribute to knowledge about children’s transition to formal schooling and received a $20 gift card in appreciation of their time. They completed questionnaires at the schools after giving consent to participate, or took questionnaires home and returned them the following day. Once consent was obtained, trained research assistants completed the early literacy and behavioral self-regulation measures in quiet areas of the school across multiple testing sessions lasting between 10 and 40 minutes, depending on the school schedule and the child’s attentional capacity. The current study included the assessment of early literacy skills (TOPEL) and behavioral self-regulation (the HTKS and the Peg Tapping Task: PTT) at T1 and T2. Parents (T1 only) and teachers (T1 and T2) completed a range of self-regulation measures (see below), and parents also completed a demographic background questionnaire in the fall. 6.3. The HTKS at T1 and T2 Children were administered the 20-item HTKS that assessed three aspects of behavioral self-regulation: attention, working memory, and inhibitory control (Cameron Ponitz et al., 2009; McClelland et al., 2007).2 The first 10 test items use two commands (“touch your head,” and “touch your toes”), and two additional commands (“touch your shoulders” and “touch your knees”) are added in the last 10 test items, requiring children to follow a total of four paired behavioral commands. The task was introduced to children during a training period during which children received feedback about their performance. This was followed by four practice items and then the first 10 test items were administered. During the sec-

2 The HTKS was initially developed as a 10-item measure which included only commands to “touch your head” and “touch your toes” (Cameron Ponitz et al., 2008; McClelland et al., 2007). The current study used the 20-item version of the HTKS which added two commands (i.e., “touch your knees” and “touch your shoulders”) and 10 additional items (Cameron Ponitz et al., 2009; McClelland & Cameron, 2012). The 20-item HTKS differs from the more recent 30-item HTKS-Extended (Becker et al., 2014; McClelland et al., 2014; Schmitt et al., 2015), which added 10 more items and an additional rule switch.

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ond half of testing, children were trained on the two additional commands and were provided feedback about their responses. Again, four practice items were administered, followed by the last 10 test items. The test is adaptive in nature, such that the last 10 test items are only administered to children who respond correctly (including self-corrects) to five or more of the first 10 test items, or if the child is in kindergarten or older.2 Given our sample of kindergarteners, we administered all 20 test items to all children. No feedback about performance was provided when test items were administered. Children receive scores of 0 (incorrect), 1 (selfcorrect), or 2 (correct) for each item. A self-correct is defined as any motion towards the incorrect response followed by the correct response. A total score was computed by summing the response for each item. Scores range from 0 to 40, with higher scores indicating higher levels of behavioral self-regulation. The internal consistency, estimated using Cohen’s alpha, was .96 at T1 and .95 at T2. The testretest reliability, estimated using the correlation between the HTKS total scores at T1 and T2 was r = .52, p < .01. 6.4. Criterion measures for convergent validity The criterion measures for convergent validity included behavioral, parent, and teacher measures that were specified as indicators of a latent variable of “cool” aspects of self-regulation in the confirmatory factor analyses (see Figs. 1 and 2). 6.4.1. The Peg Tapping Task at T1 and T2 Children were administered the Peg Tapping Task (PTT; Diamond & Taylor, 1996) mentioned above. Children completed 16 test trials that were scored 0 for an incorrect response and 1 for a correct response. The PTT total scores ranged from 0 to 16 (˛ = .95 at T1 and ˛ = .87 at T2).3 However, the PTT scores at T2 reached the ceiling (M = 15.07 out of 16; see Table 2), and thus were not included in the analyses. 6.4.2. Parents’ ratings of working memory problems at T1 Parents completed the 17-item working memory subscale of the Behavior Rating Inventory of Executive Function − Preschool Version (BRIEF-P; Gioia, Epsy, & Isquith, 2003; e.g., “has trouble remembering something, even after a brief period of time”; ˛ = .93). Items were rated on a three-point Likert scale (never, sometimes, often), with higher scores indicating poorer working memory. The BRIEF has demonstrated strong reliability, validity, and internal consistency in previous studies with children two to five years old from different ethnic and socioeconomic backgrounds (Isquith, Gioia, & Epsy, 2004). 6.4.3. Parents’ (T1 only) and teachers’ ratings (T1 and T2) of attention focusing and inhibitory control Parents and teachers completed the attention focusing and inhibitory control subscales of the Child Behavior Questionnaire (CBQ) short-form (Putnam & Rothbart, 2006; Rothbart, Ahadi, Hershey, & Fisher, 2001) using a 7-point Likert scale ranging from 1 (“extremely untrue”) to 7 (“extremely true”). The CBQ has demonstrated strong reliability and validity in studies of children from various cultural and ethnic groups (Cameron Ponitz et al., 2009; Putnam & Rothbart, 2006; Rudasill, Gallagher, & White, 2010). The attention focusing subscale included six items (e.g., “will move from one task to another without completing any of them;” ˛ = .67 for

3 It should be noted that the PTT has been scored differently than the original task in previous studies, making cross study comparisons difficult. For instance, the PTT was used in Head Start FACES (2009) during which scores reflect the percentage of times the child tapped correctly and thus could take on any value from zero to 100, with higher scores indicating better performance.

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parents at T1, and .86 and .85 for teachers at T1 and T2), whereas the inhibitory control subscale contained six items (e.g., “can wait before entering into new activities if s/he is asked to;” ˛ = .56 for parents at T1, and .85 and .79 for teachers at T1 and T2).4 6.4.4. Teachers’ ratings of inattention at T1 and T2 Teachers completed the inattention subscale of the Conners’ Teacher Rating Scale (Conners, 1997) for preschool children (CTRS15; Purpura & Lonigan, 2009). The inattention subscale has 5 items (e.g., “fails to finish things she/he starts”; ˛ = .92 and .91 at T1 and T2) rated on a 4-point scale from 0 (“never/not at all”) to 3 (“very often/frequently”). 6.5. Criterion measures for discriminant validity The criterion measures for discriminant validity included parent and teacher measures that were specified as indicators of a latent variable of “hot” aspects of self-regulation (see Figs. 1 and 2). 6.5.1. Parents’ ratings of emotional control problems at T1 Parents completed the 10-item emotional control subscale of the BRIEF-P (Gioia et al., 2003; e.g., “becomes upset too easily”; ˛ = .93). Items were rated on a three-point Likert scale (never, sometimes, often), with higher scores indicating poorer emotional control. 6.5.2. Parents (T1 only) and teachers’ ratings (T1 and T2) of impulsivity Parents and teachers completed the impulsivity subscale of the CBQ short-form (Putnam & Rothbart, 2006; Rothbart et al., 2001). The impulsivity subscale included 6 items (e.g., “usually rushes into an activity without thinking about it”; ˛ = .74 for parents at T1, and .71 and .65 at T1 and T2 for teachers). 6.6. Criterion measure for predictive validity 6.6.1. Early literacy skills Trained research assistants administered the Test of Preschool Early Literacy (TOPEL; Lonigan et al., 2007), a nationally normed and standardized measure of early literacy skills, twice, first in the fall (T1) and then in the spring (T2). The TOPEL assesses print knowledge such as print concepts, letter discrimination, word discrimination, sound name, and letter name; definitional vocabulary, i.e., the ability to define words and use single-word spoken vocabulary; and phonological awareness, i.e., children’s ability to manipulate sound units. The TOPEL has demonstrated high internal consistency and test-retest reliability, high inter-scorer agreement, and good criterion validity (Lonigan et al., 2007), and yielded satisfactory overall internal consistency in the current study (˛ = .95 and .92 at T1 and T2). 7. Results 7.1. Missing data Fifteen children had some missing values in parent or teacher ratings. Thirteen children left the schools and did not participate in the T2 assessment. Multiple imputation was used to compute missing values (Schaffer, 1997). Specifically, the EM algorithm and method of generating random numbers from probability distributions with the Markov chains (Markov Chain Monte Carlo; Du Toit &

4 The teacher-report inhibitory control subscale contained five items. One item was eliminated (i.e., “prepares for trips and outings by planning things s/he will need”) because most teachers indicated that they did not have a chance to observe children in this situation and thus chose “not applicable.”

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Table 1 Descriptive statistics by Native Hawaiian heritage. Variable

Child age (months) Mother’s educationa Father’s educationa T1 HTKS T2 HTKS T1 PTT T2 PTT T1 TOPEL T2 TOPEL T1 CBQ impulsivity (T) T2 CBQ impulsivity (T) T1 CBQ attention focusing (T) T2 CBQ attention focusing (T) T1 CBQ inhibitory control (T) T2 CBQ inhibitory control (T) T1 CTRS inattention (T) T2 CTRS inattention (T) T1 CBQ impulsivity (P) T1 CBQ attention focusing (P) T1 CBQ inhibitory control (P) T1 BRIEF working memory (P) T1 BRIEF emotional control (P)

Native Hawaiian (n = 71)

Non-Hawaiian (n = 49)

M

SD

Range

M

SD

Range

F

59.37 3.96 3.58 14.39 26.83 8.87 14.56 85.65 113.93 3.97 4.10 4.42 4.54 4.83 4.95 1.05 0.86 3.64 4.79 4.52 0.54 0.54

5.20 1.14 0.91 13.46 11.59 6.13 2.28 19.68 12.25 1.17 1.07 1.31 1.30 1.34 1.23 0.94 0.78 1.07 0.94 0.85 0.37 0.52

52–77 2–6 2–6 0−39 0−40 0−16 4–16 29–121 58–129 1–6.33 1.50−6.67 1.67−6.83 1.5–7.0 1–7 1–7 0−3 0−3 1–6.17 2.33−6.67 1.83−6.50 0−1.71 0−1.90

60.33 4.43 4.17 19.69 29.98 12.37 14.67 97.67 119.02 3.79 3.78 5.02 5.07 5.23 5.12 0.59 0.49 3.49 5.09 4.97 0.42 0.51

4.67 1.31 1.34 14.37 11.17 4.55 2.69 20.15 9.08 1.11 1.06 1.23 1.25 1.28 1.18 0.80 0.64 1.16 0.99 0.93 0.38 0.50

52–76 1–6 1–6 0−39 0−40 0−16 0−16 7–125 91–130 1.83−6 1.33−6.17 1.33−6.67 2.33−7 1.6–7 3–7 0−2.6 0−2.6 1.33−5.67 2.83−7 2.5–6.83 0−1.59 0−2

1.44 3.90* 6.67* 4.19* 3.43 13.44** 0.04 13.43** 6.52* 1.01 2.08 3.95* 2.58* 3.69* 2.89* 5.10** 5.08** 1.22 3.10* 4.87** 1.89 1.64

Note. T = teacher rating, P = parent rating. HTKS = Head–Toes–Knees–Shoulders task; PTT = Peg Tapping Task; TOPEL = Test of Preschool Early Literacy; CBQ = Child Behavior Questionnaire; CTRS = Conners’ Teacher Rating Scale; BRIEF = Behavior Rating Inventory of Executive Function. a Parent education is coded as 1 = elementary–6th grade, 2 = 7th–8th grade, 3 = 9th–12th grade, 4 = 1–2 years of college, 5 = 3–4 years of college, 6 = college graduate or higher. * p < .05. ** p < .01. Table 2 Descriptive statistics by gender. Variable

Child age (months) Mother’s educationa Father’s educationa T1 HTKS T2 HTKS T1 PTT T2 PTT T1 TOPEL T2 TOPEL T1 CBQ impulsivity (T) T2 CBQ impulsivity (T) T1 CBQ attention focusing (T) T2 CBQ attention focusing (T) T1 CBQ inhibitory control (T) T2 CBQ inhibitory control (T) T1 CTRS inattention (T) T2 CTRS inattention (T) T1 CBQ impulsivity (P) T1 CBQ attentional focusing (P) T1 CBQ inhibitory control (P) T1 BRIEF working memory (P) T1 BRIEF emotional control (P)

Girl (n = 58)

Boy (n = 62)

F

M

SD

Range

M

SD

Range

59.45 4.09 3.94 18.34 29.26 11.36 15.07 92.83 116.78 3.69 3.71 5.04 5.07 5.40 5.37 0.58 0.47 3.33 5.19 4.90 0.40 0.41

4.91 1.28 1.17 14.26 11.31 5.18 1.53 22.89 11.27 1.13 0.88 1.31 1.21 1.15 1.11 0.78 0.57 1.04 0.94 0.83 0.35 0.43

52–77 1–6 2–6 0−39 0−40 0−16 8–16 7–125 58–130 1.5–6 1.50−5.33 1.33−6.83 2.17−7 2–7 2.60−7 0−2.60 0−1.80 1–5.17 2.83−7 2.50−6.67 0−1.59 0−1.80

60.05 4.20 3.72 14.89 27.05 9.31 14.18 88.44 115.29 4.10 4.21 4.32 4.46 4.61 4.69 1.12 0.93 3.81 4.66 4.52 0.57 0.63

5.09 1.19 1.11 13.71 11.61 6.18 3.02 18.27 11.38 1.14 1.18 1.22 1.33 1.37 1.21 0.95 0.82 1.12 0.92 0.94 0.39 0.55

52–75 3–6 1–6 0−39 0−40 0−16 0−16 48–119 59–130 1–6.33 1.33−6.67 1.5–6.67 1.50−7 1–7 1–7 0−3 0−3 1.17−6.17 2.33−6.33 1.83−6.83 0−1.71 0−2

0.91 0.21 0.83 1.39 1.20 2.23 4.66* 0.77 0.12 2.80 4.14* 6.59** 4.28* 8.89** 8.27** 7.86** 8.33** 3.55 7.53** 5.10* 2.86 4.83*

Note. T = teacher rating, P = parent rating. HTKS = Head–Toes–Knees–Shoulders task; PTT = Peg Tapping Task; TOPEL = Test of Preschool Early Literacy; CBQ = Child Behavior Questionnaire; CTRS = Conners’ Teacher Rating Scale; BRIEF = Behavior Rating Inventory of Executive Function. a Parent education is coded as 1 = elementary–6th grade, 2 = 7th–8th grade, 3 = 9th–12th grade, 4 = 1–2 years of college, 5 = 3–4 years of college, 6 = college graduate or higher. * p < .05. ** p < .01

Du Toit, 2001) was applied using LISREL 8.70. The following results are based on the data following multiple imputation. 7.2. Psychometric analyses of the HTKS 7.2.1. Confirmatory factor analysis Since the practice of calculating a total HTKS score across items is built upon the assumption of unidimensionality, we constrained

all the items to one latent factor and examined model fit using the “laavan” package (Rosseel, 2012) in the statistical programming language R (R Core Team, 2014). When choosing model fit indices, we took into account both the oversensitivity of the chi-square goodness-of-fit estimate (Browne, MacCallum, Kim, Andersen, & Glaser, 2002), and our relatively small sample size, which according to Hu and Bentler (1998), may yield a large range of Tucker-Lewis Fit Index (TLI) and over-rejection of true-population models by

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Root Mean Square Estimate Approximation (RMSEA). Therefore, we included four fit estimators using the cut-offs suggested by Hu and Bentler (1999), Comparative Fit Index (CFI) and TLI values above .95, RMSEA value close to .06, and Standardized Root Mean Square Residual (SRMR) value close to .08. Although the values of RMSEA and SRMR were slightly higher than the recommended values, overall the one-factor model had reasonable fit at T1 (2 (170) = 305.64, p < .001; CFI = .99, TLI = .99, RMSEA = .08, SRMR = .09) and T2 (2 (170) = 174.67, p = .39; CFI = 1.00, TLI = 1.00, RMSEA = .02, SRMR = 0.09). Given that at least two of the four fit indices used were within the criterion values, the results can be reasonably interpreted using the two-index strategy recommended by Hu and Bentler (1998). 7.2.2. Item characteristic curves Given the unidimensionality of the HTKS, we further examined item properties based on item characteristic curves (ICCs). Using the “ltm” package (Rizopoulos, 2006) in R, we applied a 2parameter model (Birnbaum, 1958, 1968) that specifically assessed item difficulty and item discrimination, to T1 and T2 HTKS item scores separately. Items from T1 had difficulty parameters ranging from −.60 to 1.04 and discrimination parameters that ranged between 1.21 and 4.89. Items from T2 had difficulty parameters ranging between −1.44 and .34 and discrimination parameters that ranged between .94 and 5.39. Taken together, item difficulties were within one standard deviation at both T1 and T2, and item discrimination parameters were above .8, suggesting that all items achieved satisfactory properties (Walstad and Robson, 1997). Please see Figs. S1 and S2 in the Supplemental Material for plots of the ICCs at T1 and T2, respectively. 7.2.3. Differential item function To examine whether the HTKS items functioned similarly or differently for children with or without Native Hawaiian heritage, we used the “difR” package (Magis, Beland, Tuerlinckx, & De Boeck, 2010) in R, and conducted differential item function (DIF) analyses with the HTKS data at both T1 and T2. Using Lord’s method (Logistic Ordinal Regression Differential Item Functioning; Crane, Gibbons, Jolley, & van Belle, 2006) on a graded response model (Samejima, 1969) we compared chi-square differences on discrimination parameters. For the T1 HTKS scores, chi-square values ranged between .03 and .98. The results did not contain any items with statistically significant chi-square values that would represent DIF. For the T2 HTKS scores, DIF could not be calculated due to insufficient (fewer than five) categorical responses for the score of “1” (i.e., self-correction) on items 8, 10, and 12. 7.3. Comparisons of Native Hawaiian/non-Hawaiian children to other United States and international samples To highlight the importance of examining behavioral selfregulation and its relation to school readiness such as early literacy skills among rural Native Hawaiian children, we conducted a series of comparisons on self-regulation (HTKS), and early literacy skills (TOPEL), drawing data from publicly available databases and publications. 7.3.1. HTKS Among the studies we identified in the literature that used the HTKS, five U.S. samples (Duncan et al., 2017; Lan et al., 2011; Lillard, 2012; McClelland et al., 2014; Schmitt et al., 2014) and seven international samples (Cadima et al., 2015; Cadima, Verschueren, Leal, & Guedes, 2016; Lan et al., 2011; Son et al., 2013; von Suchodoletz et al., 2013; Wanless, McClelland, Acock et al., 2011; Wanless et al., 2013) were comprised of children of a comparable age to the current sample (60 months ± 2 months). The U.S. samples were mostly

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White English- or Spanish-speaking children from low- to middleclass families, with the average HTKS scores ranging from 15.32 for a mixed sample of Head Start and non-Head Start children (Duncan et al., 2017) to 24.93 for a sample of mostly White children (Lillard, 2012), in comparison to average scores of 14.39 for Native Hawaiian and 19.36 for non-Hawaiian children at T1. The children from international samples had average HTKS scores ranging from 19.51 among Portuguese children (Cadima et al., 2015) to 32.60 among Chinese children (Wanless et al., 2013). 7.3.2. TOPEL The TOPEL was normed on a sample of 842 three-to-five years old children by Longian et al. (2007), including European Americans (M = 102 on the overall Early Literacy Index [ELI]), African Americans (M = 92), and Hispanic Americans (English Only, M = 102; Bilingual, M = 84). In comparison, the average ELI scores were 85.65 for Native Hawaiian children and 97.67 for non-Hawaiian children at T1. Thus, Native Hawaiian children, though on average being older, had comparable overall TOPEL ELI scores to those of Bilingual Hispanic children (t = −.59, p = .56), but their scores were lower than other ethnic groups (ts ranged from 2.42 to 6.79, ps range from .00 to .02) in the normed sample. 7.4. Comparisons between Native Hawaiian and non-Hawaiian children and across gender We conducted a series of 2 × 2 ANOVAs to examine the main effects of Native Hawaiian heritage and gender, as well as the interaction between the two. As shown in Table 1, compared to Native Hawaiian children, non-Hawaiian children had higher HTKS and PTT scores at T1, higher TOPEL scores at T1 and T2, higher parents’ ratings of attention focusing and inhibitory control, higher teachers’ ratings of attention focusing and inhibitory control at T1 and T2, and lower teachers’ ratings of inattention at T1 and T2. NonHawaiian children’s mothers and fathers also had more years of education. As shown in Table 2, compared to boys, girls had higher PTT scores at T2, higher teachers’ ratings of attention focusing and inhibitory control, and lower teachers’ ratings of inattention at T1 and T2. Girls also had higher parents’ ratings of attention focusing and inhibitory control, and lower parents’ ratings of emotional control problems at T1. We did not find any significant interaction between Native Hawaiian heritage and gender. 7.5. Correlation analyses Due to the large number of variables and to match the analyses of convergent and discriminant validity below, we reported two sets of correlational analyses, first among the HTKS and other criterion measures of convergent and predictive validity, and then among the HTKS and criterion measures of discriminant validity. As shown in Table 3, children’s HTKS scores at T1 were positively related to their PTT scores at T1 and T2 (rs = .57, .21, ps < .05), TOPEL scores at T1 and T2 (rs = .58, .44, ps < .01), teachers’ ratings of attention focusing at T1 and T2 (rs = .34, .20, ps < .05), teachers’ ratings of inhibitory control at T1 (r = .38, p < .01), and parents’ ratings of attention focusing (r = .33, p < .01) and inhibitory control (r = .26, p < .01) at T1, and were negatively correlated with teachers’ ratings of inattention at T1 and T2 (rs = −.43, −.33, ps < .01), and parents’ ratings of working memory problems at T1 (r = −.33, p < .01). Children’s HTKS score at T2 was positively related to their PTT scores at T1 and T2 (rs = .44, .33, ps < .01), TOPEL scores at T1 and T2 (rs = .48, .47, ps < .01), teachers’ ratings of attention focusing at T1 and T2 (rs = .32, .20, ps < .05), teachers’ ratings of inhibitory control at T1 and T2 (rs = .25, 21, ps < .05), and parents’ ratings of attention focusing at T1 (r = .26, p < .01), and were negatively correlated with

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Table 3 Correlations between the HTKS and criterion measures of convergent and predictive validity.

1. T1 HTKS 2. T2 HTKS 3. T1 PTT 4. T2 PTT 5. T1 TOPEL 6. T2 TOPEL 7. T1 CBQ attention focusing (T) 8. T2 CBQ attention focusing (T) 9. T1 CBQ attention focusing (P) 10. T1 CBQ inhibitory control (T) 11. T2 CBQ Inhibitory Control (T) 12. T1 CBQ inhibitory control (P) 13. T1 CTRS inattention (T) 14. T2 CTRS inattention (T) 15. T1 BRIEF working memory (P)

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

– .52** .57** .21* .58** .44** .34** .20* .33** .38** .14 .26** −.43** −.33** −.33**

– .44** .33** .48** .47** .32** .20* .26** .25** .21* 0.17 −.30** −.37** −.25**

– .33** .51** .41** .44** .23* .29** .46** .28** 0.18 −.56** −.40** −.25**

– .45** .39** .26** .12 .32** .21* .20* 0.13 −.24** −.17 −.31**

– .64** .36** .16 .27** .31** .16 .23* −.49** −.34** −.15

– .21* .12 .17 .19* .16 0.09 −.23* −.36** −.15

– .72** .37** .82** .56** .33** −.80** −.64** −.44**

– .34** .62** .75** .21* −.59** −.78** −.37**

– .30** .26** .53** −.31** −.31** −.57**

– .61** .26** −.80** −.65** −.38**

– .21* −.53** −.72** −.31**

– −.25** −.14 −.38**

– .69** .30**

– .38**

–

Note. T = teacher rating; P = parent rating; HTKS = Head–Toes–Knees–Shoulders task; PTT = Peg Tapping Task; TOPEL = Test of Preschool Early Literacy; CBQ = Child Behavior Questionnaire; CTRS = Conners’ Teacher Rating Scale; BRIEF = Behavior Rating Inventory of Executive Function. * p < .05. ** p < .01. Table 4 Correlations between the HTKS and criterion measures of discriminant validity.

1. T1 HTKS 2. T2 HTKS 3. T1 CBQ impulsivity (T) 4. T2 CBQ impulsivity (T) 5. T1 CBQ impulsivity (P) 6. T1 BRIEF emotional control (P)

1

2

3

4

5

6

– .52** .01 −.00 −.21* −.21*

– .10 .02 −.11 −.11

– .65** .15 .07

– .19* .05

– .43**

–

Note. T = teacher rating; P = parent rating; HTKS = Head–Toes–Knees–Shoulders task; CBQ = Child Behavior Questionnaire; BRIEF = Behavior Rating Inventory of Executive Function. * p < .05. ** p < .01.

teachers’ ratings of inattention at T1 and T2 (rs = −.30, −.37, ps < .01), and parents’ ratings of working memory problems at T1 (r = −.25, p < .01). Table 4 shows that children’s HTKS scores at T1 were negatively related to parents’ ratings of impulsivity (r = −.21, p < .05) and emotional control problems (r = −.21, p < .05), whereas HTKS scores at T2 were not related to any other criterion measures of discriminant validity. 7.6. Convergent and discriminant validity To examine the convergent and discriminant validity of the HTKS at T1 and T2 respectively, we conducted confirmatory factor analyses using the “laavan” package (Rosseel, 2012) in R with the weighted least squares estimator (WLSMV). Specifically, in both T1 and T2 models (see Figs. 1 and 2), the HTKS and the criterion measures for convergent validity were specified to measure the latent variable of “cool” aspects of self-regulation, whereas the criterion measures for discriminant validity were specified to measure the latent variable of “hot” aspects of self-regulation. In addition, to take into account shared method variance, error terms for measures of the same informant (behavioral, teacher, parent) were allowed to be correlated. A good model fit would provide evidence for both convergent and discriminant validity. As shown in Figs. 1 and 2, the T1 model fit the data reasonably well: 2 (31) = 35.88, p = .25; CFI = .99, TLI = .99, RMSEA = .04 and SRMR = .07, but the T2 model, which only had one criterion measure for the “hot” aspect of self-regulation, had poorer fit: 2 (1) = 3.39, p = .07; CFI = .99, TLI = .86, RMSEA = .14 and SRMR = .04. The latent relation between “cool” and “hot” aspects of self-regulation was .76, p < .01 at T1 and .49, p < .01 at T2. Given the substantial rela-

tion between “cool” and “hot” aspects of self-regulation at T1, we tested an alternative one-factor model that did not distinguish “hot” from “cool” aspects of self-regulation. This alternative model yielded a comparable fit: 2 (32) = 36.43, p = .27; CFI = .99, TLI = .99, RMSEA = .03 and SRMR = .07. To further examine whether the evidence for convergent and discriminant validity found at T1 similarly applied to both Native Hawaiian and non-Hawaiian children (i.e., whether there was evidence for measurement invariance across the two groups), we conducted a multi-group confirmatory factor analysis, where the same two-factor model of “cool” and “hot” aspects of selfregulation was specified for both groups. Overall this multi-group two-factor model yielded satisfactory fit: 2 (62) = 57.65, p = .63; CFI = 1.00; TLI = 1.00; RMSEA = .04, SRMR = .09. 7.7. Predictive validity Given the theoretical models and empirical studies that have linked behavioral self-regulation skills, such as attention, working memory, and inhibitory control, to early literacy development (Blair & Razza, 2007; Cameron Ponitz et al., 2009; McClelland et al., 2006; McClelland & Cameron, 2012), we conducted path analyses of T1 and T2 HTKS scores and TOPEL scores in a cross-lagged model (see Fig. 3), after controlling for children’s age, gender, Native Hawaiian heritage, and parents’ average education (i.e., allowing them to have direct effects on all the HTKS and TOPEL variables). However, model fit cannot be estimated for this just-identified model with zero degree of freedom. Therefore, we removed nonsignificant paths that involved a control variable and re-ran the path analyses. The path model, which only included parents’ education as a control variable, fit the data reasonably well: 2 (2) = .02, p = .99; CFI = 1.00, TLI = 1.00, RMSEA = .00, SRMR = .01. However, the path from the HTKS at T1 to the TOPEL at T2 was not significant. Parents’ education was positively related to the HTKS and TOPEL scores at T1 (.28, and .23, ps < .01) but not at T2. 8. Discussion 8.1. Psychometric properties of the HTKS The current study extended previous findings and provided initial support for the psychometric properties and validity of the HTKS with a sample of rural, indigenous and multiethnic children that have been clearly underrepresented in the literature. Consistent with previous studies of other ethnic groups, psychometric

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analyses showed that when being used with Native Hawaiian and non-Hawaiian children from a rural community, the HTKS was unidimensional and internally consistent. In addition, the item parameters were satisfactory, based on analyses of item characteristic curves (ICCs) at T1 and T2, and, none of the HTKS items had DIF at T1 when being used with Native Hawaiian and non-Hawaiian children. To our knowledge, this was the first time that the HTKS items were analyzed within an Item Response Theory (IRT) framework, and our findings provided further support for using the HTKS with children from minority and indigenous cultural groups. 8.2. Comparisons of Native Hawaiian children to non-Hawaiian children and other United States and international samples of comparable age When being compared to non-Hawaiian children, other samples from the United States, and foreign children of comparable age in previous studies, overall, Native Hawaiian children exhibited lower behavioral self-regulation and early literacy skills, particularly at the time they entered kindergarten (T1), highlighting the at-risk status of Native Hawaiian children and the importance of developing their behavioral self-regulation skills as they begin formal schooling. It should be noted that unlike ELI standard scores of the TOPEL, the HTKS scores were unstandardized raw scores, making cross study comparisons difficult. There is a clear need to develop normative information and standard scores adjusted for age for the HTKS to aid in understanding the comparability of the measure across cultural groups. In addition, SES and race/ethnicity tend to be confounded so it is hard to identify the source of these differences. Thus, despite the different average HTKS scores for other ethnic or cultural groups, our data cannot directly address the key question regarding how the HTKS scores for Native Hawaiians are similar to, or different from, other ethnic or cultural groups. Native Hawaiian children did not differ from non-Hawaiian children in literacy skills and most measures of behavioral selfregulation, including the HTKS at T2, with the exception of teachers’ ratings of attention focusing and inattention problems. With maturation and some experience of formal schooling, Native Hawaiian children seemed to have made up some ground, particularly in their performance on behavioral measures of self-regulation and early literacy skills. However, these findings may be partly due to the problem of ceiling effect at T2 for some behavioral measures, particularly the PTT, which limited the ability to differentiate older children of varying self-regulation and literacy skills. Given the lower teachers’ ratings of attention focusing at T2, it is important to evaluate Native Hawaiian children’s self-regulation using additional behavioral measures that are appropriate for older children. 8.3. Convergent and discriminant validity Consistent with previous studies (e.g., Cameron Ponitz et al., 2009; Fuhs et al., 2015, Lonigan, Lerner, Goodrich, Farrington, & Allan, 2016; Schmitt et al., 2014; Wanless, McClelland, Acock et al., 2011), the analyses of convergent validity showed that the HTKS scores are significantly related to a range of behavioral, parent, and teacher measures of children’s attention focusing, working memory, and inhibitory control, providing additional evidence that supports the HTKS as an integrated measure that assesses multiple aspects of behavioral self-regulation. Few studies have examined discriminant validity of the HTKS in relation to other measures that focus on different aspects of selfregulation. Based on the theoretical framework of “hot” and “cool” aspects of self-regulation (Zelazo & Carlson, 2012), we tested the discriminant validity of the HTKS in relation to parent and teacher measures of emotional control problems and impulsivity that seem to tap “hot” aspects of self-regulation in situations that are affec-

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tively salient. This two-factor model of self-regulation seemed to fit the data reasonably well at T1 for both Native Hawaiian and nonHawaiian children. In contrast, the model fit was unsatisfactory at T2. Moreover, an alternative one-factor model that did not distinguish “hot” from “cool” aspects of self-regulation also fit the data well at T1. Taken together, the evidence for discriminant validity was relatively weak. In their review of executive functions in childhood and adolescence, Zelazo and Carlson (2012) showed that the distinction between “hot” and “cool” executive function was well supported in studies of older children and adults, but that there was mixed evidence with regard to this distinction among young children. Some studies found that “hot” and “cool” executive function loaded onto distinct (but correlated) factors (e.g., Willoughby, Kupersmidt, Voegler-Lee, & Bryant, 2011), whereas others failed to find evidence for hot and cool factors (e.g., Allan & Lonigan, 2011, 2014). Thus, it seems possible that “. . .the distinction is only starting to emerge in this age range, consistent with a general process of increasing functional specialization of neural systems that initially are relatively undifferentiated but become more specialized with experience as part of a developmental process of adaptation. . .” (Zelazo & Carlson, 2012, p. 357). Assuming self-regulation or executive function represents a unitary factor in early childhood, to fully address the discriminant validity of the HTKS and given its usage with young children, it is important for future studies to include behavioral tasks that measure other fundamental cognitive abilities, such as concept formation, that do not require significant involvement of executive function (e.g., Clark et al., 2016). Alternatively, the weak evidence for discriminant validity might also be due to the lack of behavioral measures of “hot” aspects of self-regulation and/or a smaller number of measures of “hot” than “cool” aspects of self-regulation. In fact, because of the lack of parent-report measures of self-regulation and the removal of the PTT due to ceiling problems, there was only one teacher-report measure of “hot” aspects of self-regulation at T2 (see Fig. 2). Given this key methodological limitation, our data cannot provide conclusive evidence and future studies are clearly warranted.

8.4. Predictive validity Consistent with prior studies (Becker et al., 2014; Cameron Ponitz et al., 2009; Fuhs et al., 2014; Matthews et al., 2009; Wanless, McClelland, Acock et al., 2011), there were significant relations between the HTKS scores and children’s early literacy skills assessed in both the fall and spring semesters of kindergarten. These findings support substantial evidence that behavioral selfregulation is associated with children’s academic success in early literacy, math, and language (Blair & Razza, 2007; McClelland et al., 2007), learning related classroom behavior (Cameron Ponitz et al., 2009), and long-term academic success (McClelland et al., 2013). The HTKS scores at T1 did not significantly contribute to TOPEL scores at T2, after controlling for the stability of early literacy skills from T1 to T2. This result is in line with Cameron Ponitz et al. (2009), which found that the HTKS scores assessed at the beginning of kindergarten did not significantly predict children’s vocabulary or literacy skills in the spring, after controlling for background demographic factors and children’s achievement test scores in the fall. Thus, it seems that early self-regulation skills alone may not be adequate for sustaining continuous development of early literacy skills across the kindergarten year, particularly for at-risk populations such as indigenous and rural children. Other factors such as teachers’ employment of literacy instructional strategies (e.g., Lonigan, Farver, Phillips, & Clancy-Menchetti, 2011), or the home literacy environment (Farver, Xu, Lonigan, & Eppe, 2013; Xu, Farver, & Krieg, 2017), which were not measured here, may also play important roles in early literacy development.

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We found that girls were rated to be better regulated than boys on most teacher and parent measures of self-regulation, but, with the exception of the PTT at T2 (which had the ceiling problem), boys and girls did not differ on other behavioral measures of self-regulation. Prior studies have examined gender differences in children’s self-regulation (Gestsdottir et al., 2014; Matthews et al., 2009; Son et al., 2013), though results have been mixed. Adult informants’ gender stereotyping might partly explain the higher self-regulation ratings for girls than for boys. Alternatively, it is possible that the regulatory features assessed by teachers and parents capture a set of skills that are more characteristic of females, whereas the behavioral tasks of self-regulation assess skills that are not gender-specific. 8.5. Limitations and future directions Several limitations should be mentioned. First, the evidence for discriminant validity of the HTKS is mixed and limited. Many factors such as measurement source variation, overall unreliability or possibly the limited number of item indicators loading on some of the latent constructs, may have contributed to the relatively poor model fit. For instance, our study relied on teacher and parent ratings of impulsivity and emotional control problems, and did not have any behavioral measures of “hot” aspects of selfregulation that assess task performance in relation to rewards and punishment. Future studies should examine children’s performance on the HTKS task in relation to their performance on behavioral tasks (e.g., delayed gratification) of discriminate validity that assess “hot” aspects of self-regulation (Carlson, Davis, & Leach., 2005; Kochanska et al., 1996; Mischel et al., 1989). Second, we only assessed literacy skills as a criterion measure for predictive validity of the HTKS. Prior studies (e.g., Blair & Razza, 2007; McClelland et al., 2014) have found that children’s HTKS scores predicted math, but not literacy achievement at the end of kindergarten. While our study did not assess early mathematics achievement, those who have included measures of both literacy and math have suggested that children’s self-regulation might foster learning across a variety of aspects of academic achievement during early schooling and might become domain specific during kindergarten as children encounter different types of demands (Fuhs et al., 2014; McClelland et al., 2014; Cameron Ponitz et al., 2009; Schmitt et al., 2014). Third, the differences found between Native Hawaiian and nonHawaiian children may be confounded by parents’ education (i.e., Native Hawaiian children’s lower self-regulation and literacy skills may be partly due to the poorer educational backgrounds of their parents). In fact, when both parents’ education and Native Hawaiian heritage were included in the path analyses, only parents’ education was significantly associated with the HTKS and TOPEL scores at T1. Thus, it is possible that the samples of Native Hawaiian and non-Hawaiian children were less different than they appeared due to the confounding effects of SES and ethnicity. Additional efforts are needed to “unpack” cultural practices of Native Hawaiian families and identify factors, other than parents’ education that may be predictive of emerging behavioral self-regulation among rural Native Hawaiian children. Moreover, to further understand similarities and differences in self-regulation between Native Hawaiian and non-Hawaiian children, it would be important to extend invariance analyses across time and to fully test group means as well as relations between the HTKS and other criterion variables in large samples. Fourth, our results should be qualified by some unique attributes of the current sample, which includes kindergarten children of multi-ethnic, part-Native Hawaiian backgrounds. It should be noted that the primary purpose of the current study was not to generalize specific findings; rather our goal was to explore

the possibility of applying a well-known, easy-to-use measure of behavioral self-regulation to an indigenous rural population that is very hard to reach and significantly underrepresented in the literature. Given the study goal of examining the short transitional period to kindergarten, the current sample has a narrow age range and future studies should examine the utility of the HTKS with a wider age range of Native Hawaiian youth. Moreover, due to the modest sample size, the results of IRT and SEM analyses need to be replicated with larger samples. In summary, consistent with previous research of children of various socioeconomic, ethnic, and cultural backgrounds (Graziano et al., 2015; von Suchodoletz et al., 2013; Wanless, McClelland, Acock et al., 2011; Wanless et al., 2013), our results provide preliminary support for using the HTKS among Native Hawaiian and non-Hawaiian children from rural communities. Our results indicate the HTKS may provide important information on children’s early developing self-regulation skills that may be instrumental for educators to develop curricula that explicitly target the promotion of self-regulation skills, and thus early achievement. Interventions that specifically focus on child skill development during early school years, such as the Tools of Mind curriculum (Bodrova & Leong, 2007) and the Preschool Promoting Alternative Thinking Strategies (PATHS; Bierman, Nix, Greenberg, Blair, & Domitrovich, 2008; Domitrovich, Cortes, & Greenberg, 2007) have demonstrated some success in improving children’s academic learning through promoting their self-regulation. Additionally, professional development programs for teachers, such as the Chicago School Readiness Project (Raver et al., 2011), focused on improving children’s self-regulation and socioemotional skills by assisting teachers in improving classroom management, have been found to show improvements in children’s self-regulation and academic achievement compared to controls. There are also promising findings from classroom interventions designed to strengthen the self-regulation of at-risk children, in improving both self-regulation and academic achievement (Schmitt, McClelland, Tominey, & Acock, 2015; Tominey & McClelland, 2011). The results of the current study point to the possibility of developing similar programs and classroom curricula for underrepresented children of rural and indigenous backgrounds who often fall behind early in their academic achievement. Better understanding the self-regulation skills of rural and indigenous youth will allow for resources to support the development of these skills, improve school readiness, and reduce ethnic and rural-urban academic achievement disparities. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.ecresq.2017.12. 007. References Allan, N. P., & Lonigan, C. J. (2011). Examining the dimensionality of effortful control in preschool children and its relation to academic and socioemotional indicators. Developmental Psychology, 47, 905–915. http://dx.doi.org/10.1037/ a0023748 Allan, N. P., & Lonigan, C. J. (2014). Exploring the dimensionality of effortful control using hot and cool tasks in a sample of preschool children. Journal of Experimental Child Psychology, 122, 33–47. http://dx.doi.org/10.1016/j.jecp. 2013.11.013 Barkley, R. A. (1997). Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94. http://dx.doi.org/10.1037/0033-2909.121.1.65 Baumeister, R. F., & Vohs, K. D. (2004). Handbook of self-regulation: Research, theory, and applications. New York: Guilford. Becker, D. R., Miao, A., Duncan, R., & McClelland, M. M. (2014). Behavioral self-regulation and executive function both predict visuomotor skills and early academic achievement. Early Childhood Research Quarterly, 29, 411–424. http:// dx.doi.org/10.1016/j.ecresq.2014.04.014

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