Sustained Attention in Infancy Impacts VocabularyAcquisition in Low-Income Toddlers

Patricia J. Brooks, Rachel M. Flynn, and Teresa M. Ober

1. Introduction

Children growing up in low-income families tend to have smaller vocabularies than more affluent children. This disparity in their vocabulary knowledge has been attributed to differences in the quantity and quality of child-directed speech (Hoff, 2003; Rowe, 2008, 2012), with much attention paid to the so-called “30 million word gap” in the number of words experienced by age 4 among children of households on welfare when compared with children of affluent households (Hart & Risley, 1995, 2003). Young children benefit from growing up in households where mothers have higher educational attainment (Dollaghan et al., 1999; Hoff & Tang, 2005), where learning materials are readily available, and where parents engage with their children in cognitively stimulating activities, such as shared picture book reading, that promote the development of pre-literacy and oral communication skills (Payne, Whitehurst, & Angell, 1994; Rodriguez & Tamis-LeMonda, 2011). Although research has emphasized how caregivers (especially mothers) stimulate language growth by conversing with their infants and responding sensitively and contingently to their communicative bids (Che, Brooks, Alarcon, Yannaco, & Donnelly, 2018; Goldstein, King, & West, 2003; Landry, Smith, & Swank, 2006), child-level factors, such as self-regulation and the ability to sustain attention, may also contribute to individual differences in language outcomes as the development of language is connected to cognition (Perszyk & Waxman, 2018; Razza, Martin, & Brooks-Gunn, 2010; Welsh, Nix, Blair, Bierman, & Nelson, 2010).

In infancy, sustained attention to objects may serve as a proxy for executive functioning as prior research indicates a close relationship between infants’ ability to attend selectively to stimuli and other cognitive skills (Choudhury & Gorman, 2000), including executive function abilities that emerge in early childhood (Cuevas & Bell, 2014; Garon, Bryson, & Smith, 2008). The emergence of executive functions in early childhood is thought to be due to the development of two attention subsystems (Rothbart & Posner, 2001). The first is the orienting system, which allows children to orient to stimuli in the external

∗* Patricia J. Brooks is at the College of Staten Island and The Graduate Center, CUNY;Rachel Flynn is at Northwestern University; Teresa M. Ober is at The Graduate Center, CUNY. Please direct correspondence to Patricia Brooks at patricia.brooks@csi.cuny.edu.

© 2018 Patricia J. Brooks, Rachel M. Flynn, and Teresa M. Ober. Proceedings of the 42nd annual Boston University Conference on Language Development, ed. Anne B. Bertolini and Maxwell J. Kaplan, 86-99. Somerville, MA: Cascadilla Press.

environment and to shift attention. This subsystem appears to vary by age even during the first year of life (Colombo, 2001). The second is referred to as the anterior attention subsystem, and it is thought to develop later in infancy (Rothbart & Posner, 2001). This subsystem is involved in attentional processes through the selection and processing of information according to internal representations that both inhibit and facilitate the orienting subsystem. Both emerging systems influence the child’s ability to attend selectively to stimuli and focus on tasks that require executive function skills.

The flexible higher-order control of behavior that occurs during executive function tasks appears to be necessary for language development as well (Müller, Jacques, Brocki, & Zelazo, 2009). Indeed, there is evidence that during early childhood, individual differences in attention are related to language outcomes, such as vocabulary development (Bornstein & Sigman, 1986; Colombo, Shaddy, Blaga, Anderson, Kannass, & Richmond, 2009). Children appear to require foundational attentional skills in order to navigate multiple tasks and communicate verbally. Therefore, even though the quality of language inputs may in part be determined by parenting style (Tamis-LeMonda & Bornstein, 1989), parenting style and the quality of language inputs do not fully account for the observed variance in children’s language development outcomes.

The current study used longitudinal data from the control group of the Early Head Start Research and Evaluation Project (EHSRE; Love et al., 2005) to explore whether a constellation of infant and parental factors might account for significant variation in vocabulary knowledge in children growing up in low income households. The EHSRE was a longitudinal randomized-control study that evaluated the impact of enrollment in Early Head Start programs on social and cognitive outcomes from infancy through childhood. The Birth to Three Phase (1996-2001) involved the administration of comprehensive assessments related to the child’s cognitive and communicative functions, parent-child interactions, home environment, and parent and family background, collected when the children were 14, 24, and 36 months of age. Our goal was to determine the extent to which individual differences in infants’ sustained attention, assessed at 14 months in the context of semi-structured play with their mother, was predictive of their receptive vocabulary at 36 months after controlling for variables previously shown to influence language outcomes, which included parent supportiveness and the quality of the home environment. 2. Method 2.1. Participants

The sample consisted of a subset of participants recruited from low-income families for the EHSRE project (Love et al., 2005). The subset consisted of children in the control group (i.e., not enrolled in Early Head Start programs) with scores for the main variables of interest (i.e., the 3-bag task at 14 months of age and the Peabody Picture Vocabulary Test at 36 months of age) and from families that identified English as the primary language at home. Within the

87

sample (N = 411; 208 boys and 203 girls), 52.8% identified as White/Caucasian, 36.5% as Black/African-American, 6.8% as Hispanic/Latino, and 3.9% as Other. On average, family income was 62.5% (SD = 50.0) of the poverty threshold. Regarding maternal education, 38.0% of mothers had less than 12 years of schooling (score of 1), 33.8% had 12 years of schooling or a GED (score of 2), and 28.2% had more than 12 years of schooling (score of 3), M = 1.9 (SD = 0.8). 2.2. Measures

From the ESHRE dataset, measures taken at 14 months were used to predict vocabulary knowledge at 36 months. At 14 months, we used a standardized (norm-referenced) assessment of child cognitive ability, and assessments of the home environment and parent-child interaction. At 36 months, we used a standardized (norm-referenced) assessment of receptive vocabulary. 2.2.1. Bayley Mental Development Index

The Bayley Scales of Infant Development, Second Edition (BSID-II; Bayley, 1993) measure mental and motor development in infants from 1 to 42 months of age. The Bayley Mental Development Index (MDI) is a subscale of the BSID-II measuring cognitive, communicative, and social-emotional development of children under age 41 months. Standardized scores are based on population norms, µ = 100, σ = 15. 2.2.2. Home Observation for the Measurement of the Environment

The HOME inventory (Caldwell & Bradley, 1984) measures the quality of stimulation and support available to a child within the home environment. The Infant/Toddler HOME is appropriate for participants from birth to age 3 years, and consists of a combination of parental self-report items and interviewer-observed items (e.g., the quality of the mother’s speech and verbal responses to the child during the home visit, as rated by the interviewer; whether the parent encourages the child to learn shapes, colors, numbers, and the alphabet; the presence of books, toys, and games accessible to the child; and whether the parent reads to the child several times per week). Based on these observed variables, an overall composite score is derived. (Note that the EHSRE dataset does not provide norm-referenced scores for the HOME inventory.) 2.2.3. 3-Bag Task

The 3-bag task utilizes a semi-structured play protocol in which the parent-child dyad is instructed to play with the toys in each of three bags in a predetermined sequence (see Fuligni & Brooks-Gunn, 2013). For children at 1 year of age, bag 1 contained the picture book Good Dog Carl, bag 2 contained a set of kitchen utensils, pots, pans, and a stove, and bag 3 contained a Noah’s ark

88

and animal set. The semi-structured play interactions were videotaped and the parent-child behaviors scored in accordance with the 3-bag task coding scales used in the NICHD Study of Early Child Care (NICHD Early Child Care Research Network, 1999; Ware, Brady, O’Brien, & Berlin, 2000).

In the current study, we used data from four coding scales: child sustained attention, child engagement of parent, parent supportiveness, and parent intrusiveness. Possible scores for each scale ranged from 1 to 7. The child sustained attention scale assessed the extent to which children demonstrated focused attention and engagement with the book or toy set provided. Scores reflected the extent to which the child was involved vs. disorganized in attending to the objects. The child engagement of parent scale assessed the extent to which the child made communicative bids to engage with their mother and whether they expressed positive regard towards her. The parent supportiveness scale assessed maternal sensitivity, positive affect, and the extent to which they provided cognitive stimulation while interacting with their child. The parent intrusiveness scale assessed the extent to which the mother attempted to control the child rather than recognizing and respecting the child’s autonomy. 2.2.4. Peabody Picture Vocabulary Test

The Peabody Picture Vocabulary Test-Third Edition (PPVT; Dunn & Dunn, 1997) is an untimed assessment of receptive vocabulary. The test is administered verbally by an examiner who presents four pictures at a time to the child and the child is asked to point to the picture that matches a word spoken aloud. The PPVT is appropriate for participants at the ages of 2.5 years and older. The PPVT was administered to children at age 36 months. Standardized scores were derived for each participant based on population norms, µ = 100, σ = 15. 3. Results 3.1. Descriptive Statistics and Correlation Coefficients

Table 1 provides descriptive statistics for each of the measures used. Children’s scores on the Bayley MDI at 14 months (M = 98.4) approached the expected value of 100, based on the population norms. In contrast, children’s scores on the PPVT at 36 months (M = 83.0) were more than 1 SD below the expected value of 100. Indeed, 51.8% of the sample scored more than 1 SD below the population average (i.e., scores < 85) and 14.8% scored more than 2 SD below the population average (i.e., scores < 70). These data suggest that children in this low-income sample were at heightened risk of clinically significant delays in their vocabulary development.

Bayley MDI scores at 14 months did not differ as a function of child gender, t(409) = 1.57, p = .118 (boys: M = 97.5, SD = 10.8; girls: M = 99.2, SD = 10.7). In contrast, at 36 months, girls showed significantly greater vocabulary knowledge than boys as indicated by higher scores on the PPVT, t(409) = 2.48, p = .013 (boys: M = 81.1, SD = 16.6; girls: M = 85.0, SD = 15.0).

89

Table 1. Descriptive Statistics for Measures at 14 and 36 Months (N=411).

Child Age M (SD) Range

Bayley Mental Development Index 14 months 98.4 (10.8) 59–126 HOME Inventory 14 months 26.6 (3.2) 13–31 3-bag Task Child Sustained Attention 14 months 5.0 (1.0) 2–7 Child Engagement of Parent 14 months 3.9 (1.1) 1–7 Parent Supportiveness 14 months 4.0 (1.0) 1–7 Parent Intrusiveness 14 months 2.3 (1.2) 1–7 Peabody Picture Vocabulary Test 36 months 83.0 (15.9) 40–123

There were no standardized values for the HOME inventory or the 3-bag

task scales, which precluded any comparison to population norms. These measures failed to show significant effects of child gender (all t values ≤ 1.48, all p-values ≥ .138), which suggests that the home environment and the quality of parent-child interaction were not markedly different for boys and girls. Table 2. Bivariate Correlations (N=411), p-values shown in parentheses.

2. 3. 4. 5. 6. 7.

1. Maternal Education .07 (.183)

.30 (.000)

.12 (.017)

.09 (.069)

.27 (.000)

–.15 (.002)

2. Bayley MDI .13 (.007)

.24 (.000)

.18 (.000)

.21 (.000)

–.13 (.009)

3. HOME Inventory .18 (.000)

.17 (.001)

.46 (.000)

–.14 (.004)

4. 3-bag: Child Attention .32 (.001)

.47 (.000)

–.36 (.000)

5. 3-bag: Child Engagement .48 (.000)

–.13 (.011)

6. 3-bag: Parent Supportiveness –.32 (.000)

7. 3-bag: Parent Intrusiveness

We computed bivariate correlation coefficients to examine relationships

between the observed variables at 14 months (see Table 2, note Bonferroni-

90

corrected α level = .024). Given the large sample size, statistically significant correlations were often weak effects (r ≤ .30). In describing the results, we focus on correlations of moderate effect size (r ≥ .30).

Maternal education correlated with the quality of the home environment (HOME inventory), which in turn correlated with parent supportiveness (3-bag task). Within the 3-bag task, child sustained attention correlated positively with child engagement of the parent and with parent supportiveness, and negatively with parent intrusiveness. Parent supportiveness also correlated with child engagement of the parent, and negatively with parent intrusiveness. 3.2. Regression Models

We used regression models to explore longitudinal relationships between observed variables at age 14 months and receptive vocabulary at 36 months. As a preliminary analysis, we entered demographic variables as predictors of PPVT scores (see Table 3). Due to missing data for family income, the number of participants included (N = 340) was less than the full sample (N = 411). The preliminary model was statistically significant, F(4, 335) = 7.13, p < .001 and explained 7.8% of the variance in vocabulary knowledge at 36 months. The preliminary model identified significant effects of child gender, favoring girls and maternal education on PPVT scores; race/ethnicity and family income were not significant and were dropped from subsequent analyses. Table 3. Standardized Regression Coefficients for Demographic Variables Predicting PPVT Scores at 36 months (N=340).

β t p-value

Child Gender .15 2.91 .004 Race/Ethnicity –.08 –1.53 .128 Income as % of Poverty Line .09 1.62 .105 Maternal Education .18 3.37 < .001

Our next model entered the observed variables at 14 months (Bayley MDI,

HOME inventory, 3-bags task: child sustained attention, child engagement of parent, parent supportiveness, parent intrusiveness) along with child gender and maternal education as predictors of PPVT scores at 36 months. Tolerance and variance inflation factors indicated inconsequential collinearity, confirming that eight predictor variables could be entered simultaneously (Neter, Wasserman, & Kutner, 1989). The model was highly significant, F(8, 402) = 18.8, p < .001, and accounted for 27.2% of the variance in PPVT scores. As shown in Table 4, child cognition (Bayley MDI), home environment (HOME inventory), and child sustained attention (3-bag task) were statistically significant predictors of PPVT scores, over and above the effects of child gender and maternal education, which

91

remained significant. The other scales from the 3-bag task (child engagement of parent, parent supportiveness, parent intrusiveness) were not significant. Table 4. Standardized Regression Coefficients for Predictor Variables with PPVT Scores at 36 months as the Dependent Variable (N=411).

β t p-value

Child Gender .09 2.05 .041 Maternal Education .11 2.35 .019 Bayley Mental Development Index .23 5.13 < .001 HOME Inventory .16 3.27 .001 3-bag: Child Sustained Attention .21 4.17 < .001 3-bag: Child Engagement of Parent .04 .84 .403 3-bag: Parent Supportiveness .06 .93 .353 3-bag: Parent Intrusiveness –.04 –.85 .394

To isolate the unique contribution of child sustained attention at 14 months

in predicting vocabulary knowledge at 36 months, we re-ran the analysis using hierarchical regression, with child gender, maternal education, Bayley MDI, and HOME inventory entered in Block 1 and child sustained attention entered in Block 2. The hierarchical model indicated that child sustained attention explained 6.1% of the variance in PPVT scores, over and above the effects of variables entered in Block 1, ΔF(1, 405) = 33.4, p < .001. Table 5. Standardized Regression Coefficients after Removing Child Sustained Attention as a Predictor (N=411).

β t p-value

Child Gender .09 2.10 .037 Maternal Education .10 2.25 .025 Bayley Mental Development Index .25 5.67 < .001 HOME Inventory .15 3.03 .003 3-bag: Child Engagement of Parent .06 1.29 .197 3-bag: Parent Supportiveness .13 2.20 .028 3-bag: Parent Intrusiveness –.09 –1.89 .059

Given the observed moderate correlations across the 3-bag task variables

(shown in Table 2), we removed child sustained attention as a predictor and re-ran our initial model (see Table 5). The revised model was still significant, F(7,

92

403) = 18.2, p < .001, but accounted for only 24.1% of the variance in PPVT scores. With child sustained attention removed from the model, parent supportiveness became significant as a predictor of PPVT scores. The other 3-bag task variables remained non-significant. 3.3. Mediation Model

To test directly whether child sustained attention mediated the effect of parent supportiveness on vocabulary knowledge, we used the PROCESS macro in SPSS (Hayes & Preacher, 2014). Figure 1 illustrates the mediation model confirmed through this analysis, with lines indicating significant direct effects. The indirect effect of parent supportiveness on PPVT scores was tested using a bootstrap estimation approach with 1000 samples and 95% confidence intervals.

Fig. 1. Mediation model confirming the indirect effect of parent supportiveness on child vocabulary knowledge.

The mediation analysis indicated significant direct effects of parent

supportiveness (t = 9.31, p < .001) and child cognitive ability (t = 3.35, p < .001) on child sustained attention, F(5, 405) = 26.34, p < .001, R2 = 24.5%. Maternal education, child gender, and home environment were not related to child sustained attention. Whereas the direct effect of parent supportiveness on PPVT scores was not significant (t = 1.50, p = .134), the total effect of parent supportiveness was significant (t = 3.70, p < .001), due to the indirect effect mediated by child sustained attention (Z = 4.12, p < .001; β = .10, CI .05 :: .16). 4. Discussion

Children growing up in poverty may experience circumstances, such as exposure to chronic stress and neglect, that adversely impact their language development (McLoyd, 1998; Noble Houston, Kan, & Sowell, 2012). Researchers have tended to emphasize environmental factors, including the quality and quantity of child-directed speech, supportive and responsive

93

parenting strategies, and the availability of age-appropriate toys and books, in accounting for disparities in language development trajectories as a function of socio-economic status. Less research has explored how infants’ executive functioning, especially with regards to the control of attention, might explain variation in language outcomes for low-income children. In the current study, we used data from the control group of the EHSRE project to examine whether infant sustained attention, assessed during semi-structured parent-child playtime with a picture book and two toy sets, accounted for variance in receptive vocabulary knowledge measured almost two years later.

Consistent with prior research indicating that maternal education and indices on the HOME inventory are closely related to socioeconomic status and predictive of children’s emerging language and executive function abilities, (Sarsour, Sheridan, Jutte, Nuru-Jeter, Hinshaw, & Boyce, 2011), we observed maternal education and the home environment to contribute independently to children’s vocabulary knowledge at 36 months. We also replicated prior findings of preschool-age girls outperforming boys on measures of receptive vocabulary development (Bornstein, Hahn, & Haynes, 2004). Although researchers have speculated that parents may engage with girls and boys differently, for example by providing gender-stereotypes toys and activities that may differentially support language development (Leaper & Gleason, 1996), we found no evidence that parenting behaviors (i.e., supportiveness or intrusiveness) varied as a function of the child’s gender in the 3-bag task where dyads engaged with the same sets of toys.

Children’s cognitive abilities at 14 months, as indexed by scores on the Bayley MDI, showed a direct effect on PPVT scores at 36 months, as well as an indirect effect partially mediated by child sustained attention. Although the measures of child sustained attention and intellectual abilities were significantly correlated, each contributed to explaining unique variance in vocabulary knowledge, over and above effects of child gender, maternal education, and the home environment. With respect to developmental trajectories, at 14 months infants scored well within the normative range on the Bayley MDI, yet at 36 months the sample had PPVT scores significantly below population norms. The very low PPVT scores evidenced by more than 1/3 of the sample underscore the risk of delays in language development for children growing up in poverty.

Race/ethnicity and income as percentage of the poverty line were in the initial model but removed due to non-significance. However, in an earlier analysis of parenting behaviors utilizing the 3-bag task data from the full entire EHSRE dataset (i.e., intervention and control groups), Fuligni and Brooks-Gunn (2013) reported lower scores on parent supportiveness and higher scores on negative parenting behaviors for African American mothers than for European American mothers. When controlling for socio-economic status, the observed differences in parenting behaviors as a function of ethnicity were reduced by a substantial amount, but not entirely eliminated. In the context of the current study, additional analyses would be required to determine whether there was an

94

indirect effect of race/ethnicity on language outcomes mediated by parenting behaviors and/or infant sustained attention.

The results of mediation analyses confirmed that infant sustained attention at 14 months not only had a direct effect on vocabulary outcomes at 36 months, over and above the other predictors, but also mediated the relationship between parent supportiveness and subsequent vocabulary development. Understanding how children’s ability to sustain attention during toy play is impacted by parenting behaviors should be important amid concerns about the school readiness of young children from low-income families. The observed correlations between parent supportiveness, child engagement of parent, and child sustained attention suggest that bidirectional relationships exist.

Research by Yu and Smith (2016) provides direct evidence of bidirectional relationships of parent-child interaction on patterns of sustained attention. These researchers used dual eye-tracking methodology to measure both sustained attention (i.e., fixed gaze on an object of interest) and joint attention (i.e., mutual fixed gaze between dyads on the same object of interest) of 11 to 13-month-old infants engaged with a parent. They found that the length of episodes of joint attention predicted overall durations of infants’ sustained attention to objects. They also observed that parental attention towards an object extended the infant’s attention and, reciprocally, the infant’s attention towards an object extended the duration of their parent’s attention to it. Other research has shown that infants demonstrate longer bouts of sustained attention when interacting with caregivers who follow their attentional focus rather than attempt to redirect it (Miller, Ables, King, & West, 2009). Likewise, in longitudinal work (Bernier, Carlson, & Whipple, 2010), maternal sensitivity, consideration of their child’s thought processes, and support for child autonomy at 12 to 15 months predicted emerging executive functions at 18 and 26 months.

By identifying how infants’ attention contributes to their language development, our findings complement other recent work assessing the quality of parent-child interaction in relation to language outcomes of at-risk children. Hirsh-Pasek et al. (2015) examined expressive language development of 60 low-income participants in the NICHD Study of Early Child Care and Youth Development in relation to the quality of mother-child interaction. This study utilized a 3-box task that was similar to the 3-bag task of the EHSRE project. However, this task was scored for both quality and quantity of language. Hirsh-Pasek and colleagues reported that the quality of communication, as measured by joint engagement, shared routines, and fluency and connectedness was a better predictor than quantity of words of children’s language abilities a year later. This study did not measure the child’s sustained attention to the toys; hence, it is unknown whether the observed effects were mediated by the child’s abilities, as observed in our study. The lack of measurement of child-directed speech is a possible limitation of the current study, however, Hirsh-Pasek et al.’s (2015) findings suggest that quality indicators of parent speech are more important than the amount of language a child hears.

95

Projecting our findings beyond the ages of participants within the sample, we may predict that disparities would continue to widen. Studies of older children suggest bidirectional relationships between executive functioning and language development at school entry may serve as indices of school readiness. In a large-scale study of 1,046 five-year-old children from poor or near-poor families, Razza, Martin, & Brooks-Gunn (2010) reported that children’s ability to focus their attention, as assessed using the Leiter International Performance Scale (Roid & Miller, 1997), showed a concurrent relationship with their receptive vocabulary knowledge (PPVT scores). In a longitudinal study of children attending Head Start preschool, measures of executive functioning (encompassing working memory and attentional control) predicted reading achievement in kindergarten, after controlling for domain-specific abilities (Welsh, Nix, Blair, Bierman, & Nelson, 2010). Conversely, in another longitudinal study involving Head Start preschoolers, verbal abilities were predictive of gains in executive functioning, particularly response inhibition and attention shifting, over the academic year (Fuhs & Day, 2010). These mixed findings suggest the need for more research examining the relationship between language and executive functions to understand the mechanisms of its influence.

Although the models reported here did not include estimates of the children’s earlier vocabulary development, stability in language development is widely documented in the literature (Bornstein et al., 2004; Fenson, Dale, Reznick, Bates, Thal & Pethick, 1994). The EHSRE dataset includes estimates of infants’ receptive vocabulary at 14 months, obtained through parental report using the MacArthur-Bates Communicative Development Inventories (CDI: Fenson, Bates, Dale, Marchman, Reznick, & Thal, 2007). Preliminary analyses, not included in this report, indicated that receptive vocabulary (CDI) scores at 14 months were significantly correlated with PPVT scores at 36 months; adding the receptive vocabulary scores at 14 months to the regression models used to predict PPVT scores at 36 months did not alter the main findings reported here.

Our main finding that the control of attention in infancy contributes directly to children’s vocabulary growth has important implications for school readiness, as vocabulary knowledge, and oral language skills more generally, provide a critical foundation for learning to read (Muter, Hulme, Snowling, & Stevenson, 2004; Roth, Speece, & Cooper, 2002), which in turn is related to math skills and other indices of academic success (Durham, Farkas, Hammer, Tomblin, & Catts, 2007). Understanding how executive functioning contributes to disparities in verbal skills is crucial for designing effective early interventions for children growing up under conditions of economic adversity. References Bayley, Nancy (1993). Bayley Scales of Infant Development, Second Edition, Manual.

New York: The Psychological Corporation, Harcourt Brace & Company.

96

Bernier, Annie, Carlson, Stephanie M., & Whipple, Natasha (2010). From external regulation to self‐regulation: Early parenting precursors of young children’s executive functioning. Child Development, 81(1), 326-339.

Bornstein, Marc H., Hahn, Chun-Shin, & Haynes, O. Maurice (2004). Specific and general language performance across early childhood: Stability and gender considerations. First Language, 24(3), 267-304.

Bornstein, Marc H., & Sigman, Marian D. (1986). Continuity in mental development from infancy. Child Development, 57(2), 251-274.

Caldwell, Bettye M., & Bradley, Robert H. (1984). Administration manual: Home Observation for Measurement of the Environment. Little Rock, AR: University of Arkansas at Little Rock.

Che, Elizabeth S., Brooks, Patricia J., Alarcon, Maria F., Yannaco, Francis D., & Donnelly, Seamus (2018). Assessing the impact of conversational overlap in content on child language growth. Journal of Child Language, 45(1), 72-96.

Choudhury, Naseem, & Gorman, Kathleen S. (2000). The relationship between sustained attention and cognitive performance in 17-24-month old toddlers. Infant and Child Development, 9(3), 127-146.

Colombo, John (2001). The development of visual attention in infancy. Annual Review of Psychology, 52, 337–367.

Colombo, John, Shaddy, D. Jill, Blaga, Otilia M., Anderson, Christa J., Kannass, Kathleen N., & Richman, W. Allen (2009). Early attentional predictors of vocabulary in childhood. In John Columbo, Peggy McCardle, & Lisa Freund (Eds.) Infant pathways to language: Methods, models, and research directions (pp. 143-167). New York: Taylor & Francis.

Cuevas, Kimberly, & Bell, Martha A. (2014). Infant attention and early childhood executive function. Child Development, 85(2), 397-404.

Dollaghan, Christine A., Campbell, Thomas F., Paradise, Jack L., Feldman, Heidi M., Janosky, Janine E., Pitcairn, Dayna N., & Kurs-Lasky, Marcia (1999). Maternal education and measures of early speech and language. Journal of Speech, Language, and Hearing Research, 42(6),1432-1443.

Dunn, Lloyd M., & Dunn, Leota M. (1997). Peabody Picture Vocabulary Test, Third Edition. Circle Pines, MN: American Guidance Service.

Durham, Rachel E., Farkas, George, Hammer, Carol Scheffner, Tomblin, J. Bruce, & Catts, Hugh W. (2007). Kindergarten oral language skill: A key variable in the intergenerational transmission of socioeconomic status. Research in Social Stratification and Mobility, 25(4), 294-305.

Fenson, Larry, Bates, Elizabeth, Dale, Philip S., Marchman, Virginia A., Reznick, J. Steven, & Thal, Donna J. (2007). MacArthur-Bates communicative development inventories. Paul H. Brookes Publishing Company.

Fenson, Larry, Dale, Philip S., Reznick, J. Steven, Bates, Elizabeth, Thal, Donna J., & Pethick, Stephen J. (1994). Variability in early communicative development. Monographs of the Society for Research in Child Development, 59(5), i-185.

Fuhs, Mary W., & Day, Jeanne D. (2011). Verbal ability and executive functioning development in preschoolers at Head Start. Developmental Psychology, 47(2), 404-416.

Fuligni, Allison S., & Brooks-Gunn, Jeanne (2013). Mother-child interactions in Early Head Start: Age and ethnic differences in low-income dyads. Parenting: Science and Practice, 13, 1-26.

97

Garon, Nancy, Bryson, Susan E., & Smith, Isabel M. (2008). Executive function in preschoolers: A review using an integrative framework. Psychological Bulletin, 134(1), 31-60.

Goldstein, Michael H., King, Andrew P., & West, Meredith J. (2003). Social interaction shapes babbling: Testing parallels between birdsong and speech. Proceedings of the National Academy of Sciences, 100(13), 8030-8035.

Hart, Betty, & Risley, Todd R. (1995). Meaningful differences in the everyday experience of young American children. Baltimore, MD: Paul H Brookes Publishing.

Hart, Betty, & Risley, Todd R. (2003). The early catastrophe: The 30 million word gap by age 3. American Educator, 27(1), 4-9.

Hayes, Andrew F., & Preacher, Kristopher J. (2014). Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67, 451-470.

Hirsh-Pasek, Kathy, Adamson, Lauren B., Bakeman, Roger, Owen, Margaret T., Golinkoff, Roberta M., Pace, Amy, ... & Suma, Katherine (2015). The contribution of early communication quality to low-income children’s language success. Psychological Science, 26(7), 1071-1083.

Hoff, Erika (2003). The specificity of environmental influence: Socioeconomic status affects early vocabulary development via maternal speech. Child Development, 74(5), 1368-1378.

Hoff, Erika, & Tian, Chunyan (2005). Socioeconomic status and cultural influences on language. Journal of communication Disorders, 38(4), 271-278.

Landry, Susan H., Smith, Karen E., & Swank, Paul R. (2006). Responsive parenting: Establishing early foundations for social, communication, and independent problem-solving skills. Developmental Psychology, 42(4), 627-642.

Leaper, Campbell, & Gleason, Jean Berko (1996). The relationship of play activity and gender to parent and child sex-typed communication. International Journal of Behavioral Development, 19(4), 689-703.

Love, John M., Kisker, Ellen E., Ross, Christine, Raikes, Helen, Constantine, Jill, Boller, Kimberly, ... & Vogel, Cheri (2005). The effectiveness of Early Head Start for 3-year-old children and their parents: Lessons for policy and programs. Developmental Psychology, 41(6), 885-901.

McLoyd, Vonnie C. (1998). Socioeconomic disadvantage and child development. American Psychologist, 53(2), 185-204.

Miller, Jennifer L., Ables, Erin M., King, Andrew P., & West, Meredith J. (2009). Different patterns of contingent stimulation differentially affect attention span in prelinguistic infants. Infant Behavior and Development, 32(3), 254-261.

Müller, Ulrich, Jacques, Sophie, Brocki, Karin, & Zelazo, Philip D. (2009). The executive functions of language in preschool children. In Adam Winsler, Charles Fernyhough, & Ignacio Montero (Eds.), Private speech, executive functioning, and the development of verbal self-regulation (pp. 53-68). New York: Cambridge University Press.

Muter, Valerie, Hulme, Charles, Snowling, Margaret J., & Stevenson, Jim (2004). Phonemes, rimes, vocabulary, and grammatical skills as foundations of early reading development: Evidence from a longitudinal study. Developmental Psychology, 40(5), 665-681.

Neter, John, Wasserman, William, & Kutner, Michael H. (1989). Applied linear regression models. Homewood, IL: Irwin.

98

NICHD Early Child Care Research Network (1999). Child care and mother-child interaction in the first three years of life. Developmental Psychology, 35(6), 1399-1413.

Noble, Kimberly G., Houston, Suzanne M., Kan, Eric, & Sowell, Elizabeth R. (2012). Neural correlates of socioeconomic status in the developing human brain. Developmental Science, 15(4), 516-527.

Payne, Adam C., Whitehurst, Grover J., & Angell, Andrea L. (1994). The role of home literacy environment in the development of language ability in preschool children from low-income families. Early Childhood Research Quarterly, 9(3-4), 427-440.

Perszyk, Danielle R., & Waxman, Sandra R. (2018). Linking language and cognition in infancy. Annual Review of Psychology. [Epub ahead of print] doi:10.1146/annurev-psych-122216-011701

Razza, Rachel A., Martin, A., & Brooks-Gunn, J. (2010). Associations among family environment, sustained attention, and school readiness for low-income children. Developmental Psychology, 46(6), 1528-1542.

Rodriguez, Eileen T., & Tamis-LeMonda, Catherine 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(4), 1058-1075.

Roid, Gale H., & Miller, Lucy J. (1997). Leiter International Performance Scale-revised: Examiners Manual. Wood Dale, IL: Stoelting.

Roth, Froma P., Speece, Deborah L., & Cooper, David H. (2002). A longitudinal analysis of the connection between oral language and early reading. The Journal of Educational Research, 95(5), 259-272.

Rothbart, Mary K., & Posner, Michael I. (2001). Mechanism and variation in the development of attentional networks. In Charles Nelson & Monica Luciana (Eds.), Handbook of Developmental Cognitive Neuroscience (pp. 353–363). Cambridge, MA: MIT Press.

Rowe, Meredith L. (2008). Child-directed speech: relation to socioeconomic status, knowledge of child development and child vocabulary skill. Journal of Child Language, 35(1), 185-205.

Rowe, Meredith L. (2012). A longitudinal investigation of the role of quantity and quality of child-directed speech in vocabulary development. Child Development, 83(5), 1762-1774.

Sarsour, Khaled, Sheridan, Margaret, Jutte, Douglas, Nuru-Jeter, Amani, Hinshaw, Stephen, & Boyce, W. T. (2011). Family socioeconomic status and child executive functions: The roles of language, home environment, and single parenthood. Journal of the International Neuropsychological Society, 17(1), 120-132.

Tamis-LeMonda, Catherine S., & Bornstein, Marc H. (1989). Habituation and maternal encouragement of attention in infancy as predictors of toddler language, play, and representational competence. Child Development, 60(3), 738-751.

Yu, Chen, & Smith, Linda B. (2016). The social origins of sustained attention in one-year-old human infants. Current Biology, 26(9), 1235-1240.

Ware, Anne, Brady, Christy, O’Brien, Claudia, and Berlin, Lisa J. (2000). 14-month child-parent interaction rating scales for the three bag assessment. Early Head Start Research and Evaluation Project. Unpublished coding manual, National Center for Children and Families. New York: Teachers College, Columbia University.

Welsh, Janet, Nix, Robert, Blair, Clancy, Bierman, Karen, & Nelson, Keith (2010). The development of cognitive skills and gains in academic school readiness for children from low-income families. Journal of Educational Psychology, 102(1), 43-53.

99

Proceedings of the 42nd annualBoston University Conference on Language Development

edited by Anne B. Bertolini and Maxwell J. Kaplan

Cascadilla Press Somerville, MA 2018

Copyright information

Proceedings of the 42nd annual Boston University Conference on Language Development© 2018 Cascadilla Press. All rights reserved

Copyright notices are located at the bottom of the first page of each paper.Reprints for course packs can be authorized by Cascadilla Press.

ISSN 1080-692XISBN 978-1-57473-086-9 (2 volume set, paperback)ISBN 978-1-57473-186-6 (2 volume set, library binding)

Ordering information

To order a copy of the proceedings or to place a standing order, contact:

Cascadilla Press, P.O. Box 440355, Somerville, MA 02144, USAphone: 1-617-776-2370, sales@cascadilla.com, www.cascadilla.com