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. Author manuscript; available in PMC: 2024 May 6.
Published in final edited form as: Infancy. 2020 Dec 30;26(2):204–222. doi: 10.1111/infa.12380

Infants’ abilities to respond to cues for joint attention vary by family socioeconomic status

Emily B Reilly 1, Isabella C Stallworthy 1, Shanna B Mliner 1, Michael F Troy 2, Jed T Elison 1,3, Megan R Gunnar 1
PMCID: PMC11071129  NIHMSID: NIHMS1989282  PMID: 33378584

Abstract

The influence of socioeconomic variability on language and cognitive development is present from toddlerhood to adolescence and calls for investigating its earliest manifestation. Response to joint attention (RJA) abilities constitute a foundational developmental milestone that are associated with future language, cognitive, and social skills. How aspects of the family home environment shape RJA skills is relatively unknown. We investigated associations between family socioeconomic status (SES) —both parent education and family percentage of the federal poverty level (FPL)— parent depressive and anxiety symptoms and infant RJA performance in a cross-sectional sample of 173 infants aged 8–18 months and their parents from a variety of socioeconomic backgrounds. Results suggest that, correcting for age and receptive language, infants in families with greater economic resources respond to relatively less redundant, more sophisticated cues for joint attention. Although parent depressive and anxiety symptoms are negatively correlated with SES, parent depressive and anxiety symptoms were not associated with infant RJA. These findings provide evidence of SES-related differences in social cognitive development as early as infancy, calling on policymakers to address the inequities in the current socioeconomic landscape of the United States.

1 |. INTRODUCTION

Alongside growing wealth and income inequality in the United States (Pew Research Center, 2020), socioeconomic differences in children’s language development and academic achievement persist. As early as 18-months, variability in parent education and occupation accounts for significant variance in language development (Fernald et al., 2013). Likewise, prior to school entry, SES is correlated with the complexity of language to which children are exposed (Hoff, 2003) and significant differences in cognitive skills (Lee & Burkam, 2002). In elementary schoolers, family SES is associated with child performance on reading, math, and science assessments (Goodman et al., 2012). These socioeconomic differences in achievement persist through the school years: high school graduation rates are higher among adolescents who have never lived in poverty (Hernandez, 2011). In the absence of broad economic reform to address these inequities, identifying early emerging markers of SES inequity may elucidate targets for intervention at a time when the brain is highly plastic. With 44% of children under age three in the U.S. growing up in families with low income (Jiang & Koball, 2018), we sought to examine whether a key social cognitive skill implicated in subsequent communicative and cognitive development varies as a function of SES during infancy.

1.1 |. Responding to joint attention

Joint attention– the sharing of attention between two individuals to the same object or event in the same moment and the awareness they are doing so (Tomasello & Carpenter, 2007)– is a key milestone in infancy. Joint attention abilities are a strong predictor of future language and social cognitive development, including theory of mind and social competence (Brooks & Meltzoff, 2015; Tomasello et al., 2005). Two joint attention skills develop in infancy: responding to attention (RJA) and initiating joint attention (IJA; Mundy & Sigman, 2006). Response to joint attention involves the infant’s ability to respond to cues from another person (e.g., eye gaze, head turn, point) to attend to an object (Scaife & Bruner, 1975). Initiating joint attention represents the infant’s use of these cues to initiate joint attention with someone (Mundy & Sigman, 2006).

Prior to the rapid development of RJA followed by IJA abilities from 9 to 18 months of age (Mundy et al., 2007), infants demonstrate basic gaze following abilities (Perra & Gattis, 2010). Theoretically, the preverbal communicative exchange in shared joint attention contexts provides a foundation for the exchange of symbolic information (i.e., language; Mundy & Sigman, 2006); evidence supports the predictive role of RJA for later language development (Morales et al., 2000; Mundy et al., 2007). Response to joint attention in infancy also predicts social-cognitive skills in early childhood, specifically, social competence at 30 months and theory of mind at age 4 (Mundy et al., 2007; Vaughan Van Hecke et al., 2012). RJA is a foundational skill for both language and cognitive development and thus warrants inquiry into potential early SES-related differences.

Tomasello and Rakoczy (2003) and Tomasello and colleagues (2005) argue that its biological basis, ubiquity across cultures, and privileged evolutionary status in human phylogeny render RJA development fairly robust to environmental variation. They posit that the development of RJA abilities likely depends largely on the presence of species-typical social experience but is otherwise relatively uninfluenced by common variation in parenting, social context, and other differences in experience. Perhaps because of this, focused investigations of the role of home environments and SES on the course of RJA development are limited. Although joint attention as a global ability may exist in a variety of different environments, evidence from developmental psychopathology (Beauchaine et al., 2018; Cicchetti & Rogosch, 1996) suggests that seemingly small variations in the quality and timing of early core skills, such as the processes through which RJA unfolds as a function of different early resource and caregiving environments, may have nontrivial cascading developmental consequences.

2 |. INFLUENCE OF SOCIOECONOMIC RESOURCES ON SOCIAL COGNITIVE DEVELOPMENT

Family SES, often indexed by family income and maternal education, is associated with variation in the structure and function of the developing brain as well as language, social, and cognitive development. SES-related differences have been demonstrated in brain areas related to language development (i.e., the left occipitotemporal and left perisylvian regions) and cognitive skills such as executive function (i.e., the prefrontal cortex; Johnson et al., 2016; Petrill & Deater-Deckard, 2004). A meta-analysis of 33 studies found associations between SES and child language development (Letourneau et al., 2013). In a sample with varied family resources, 30% of the variance in first grade language skills was explained by SES (Noble et al., 2007). Decades of research has demonstrated SES differences in academic achievement (Bradley & Corwyn, 2002) and differences in working memory related to SES have been found as early as 6 months (Lipina et al., 2005).

Socioeconomic status measures have been associated with RJA but the presence and direction of this effect differs across samples. This may be in part due to differences in measurement of RJA across studies. For example, studies that use the Early Social Communication Scales (ESCS; Mundy et al., 2003) to measure RJA accuracy while the child sits across from the experimenter at a table find that infants of mothers with less education respond more often to RJA cues (Mundy et al., 2007). However, a study that measured RJA performance in a naturalistic play setting demonstrated that infants of mothers with higher education respond to more sophisticated RJA cues (Stallworthy et al., in press). One study that used the ESCS found that infants from higher SES families were more likely to engage in IJA, but found the reverse pattern for RJA (Abels & Hutman, 2015). Studies that code the amount of time parent-child dyads spend engaging in joint attention during an interactive play session have found no differences in RJA by SES (e.g., Saxon & Reilly, 1998). Further, past studies are limited in the range of SES in their samples, as much of this research has been conducted with participants who are more affluent and educated than the general population.

3 |. INFLUENCE OF PARENT DEPRESSIVE AND ANXIETY SYMPTOMS ON SOCIAL COGNITIVE DEVELOPMENT

SES is negatively associated with adult depression and anxiety symptoms (Alvarez-Galvez & Gomez-Baya, 2017). Because parent depression and anxiety are also associated with child social and cognitive development, examining parent depressive and anxiety symptoms is necessary to differentiate between RJA associations related to SES or depressive and anxiety symptoms.

3.1 |. Depression

An extensive literature demonstrates positive relations between maternal depression and child psychopathology (Cummings & Davies, 1994) and negative associations with cognitive and emotional development (Beck, 1998), more specifically, language, intelligence (IQ), and object concept tasks (Grace et al., 2003). Depressed mothers have been found to be less interactive (Field et al., 2007) and attuned to their infants’ signals. Relatedly, infants of depressed mothers are less responsive and attentive to faces (Field et al., 2009), look less at their mothers (Boyd et al., 2006; Field et al., 1988; Reissland et al., 2005; White et al., 2011), and demonstrate fewer gaze shifts when interacting with their mothers (Væver et al., 2015).

Evidence of the effects of maternal depression on joint attention is mixed and focused primarily on IJA and time spent in joint engagement during play. Some studies find intermittent depressive symptoms are associated with less time spent engaging in joint attention (Raver & Leadbeater, 2014), but several studies report no effect of depression on IJA or amount of shared attention during play (Gaffan et al., 2010; Goldsmith & Rogoff, 1997; Henderson & Donahue Jennings, 2003; Hwa-Froelich et al., 2008). One study found that mothers with dysphoria spend less time in coordinated joint attention with their infants during play compared to mothers without dysphoria even though there were no differences in the number of infant or maternal bids to sharing attention (Goldsmith & Rogoff, 1997). Another found that depressed mothers were less likely to re-engage their toddlers during play, resulting in less interactive coordination (Jameson et al., 1997). We are not aware of any research on the relation between parent depressive symptoms and infant RJA performance in particular.

3.2 |. Anxiety

Existing evidence points to associations between parental anxiety symptoms and child behavioral problems, temperament, and psychopathology (Glasheen et al., 2010). Parent anxiety may also impact the interactive contexts in which RJA develops as maternal anxiety is associated with less sensitive and structured interactions with infants (Nicol-Harper et al., 2007) and toddlers (Zelkowitz et al., 2009). Mothers who are highly anxious also tend to smile less (Field et al., 2005) and display more exaggerated behavior often thought of as hyperarousal during play (Kaitz et al., 2010; Radloff, 1977). Greater anxiety symptoms are also associated with maternal affective withdrawal and destabilized rhythms of infant affect and attentional orienting during social exchange (Beebe et al., 2011).

Despite substantial evidence of SES-related differences in child language, social, and cognitive development, investigations of associations between SES and infant RJA are limited and demonstrate mixed results. Additionally, past studies suggest that parents experiencing depressive and anxiety symptoms may have fewer internal resources for effectively scaffolding joint attention with their infants. Evidence of infants’ reduced attention and lowered joint engagement while interacting with depressed mothers suggests that abilities to read and respond to RJA cues could be impacted by maternal depression. Further, high maternal anxiety may involve increased over-arousal during dyadic interactions, potentially limiting infants’ abilities to effectively read and respond to RJA cues.

4 |. THE CURRENT STUDY

The current study addresses key gaps in the literature by examining the impact of family SES and parent depressive and anxiety symptoms on RJA in a sample with a wide range of SES. The goal of this study was to investigate how parent education, family income as a percentage of the federal poverty level (FPL), and parental depressive and anxiety symptoms are associated with RJA performance in the first year of life. We hypothesize that (1) higher FPL and parent education will both be uniquely associated with more sophisticated RJA performance, and (2) higher parent depressive and anxiety symptoms will be jointly associated with lower RJA performance. We also examined the effects of age and receptive language on RJA abilities, to align with past work.

5 |. METHODS

5.1 |. Participants

Participants were 173 parent-infant dyads recruited from a local primary care center in St. Paul, Minnesota serving families with a wide range of incomes, including a significant proportion of lower-resource families. Families were recruited at their child’s 9-, 12-, or 15-month well child visit (Table 1; M = 12.10, SD = 2.46) and participated in the study at the clinic immediately following their well child visit. Infants were excluded if they were born before 37 weeks of gestation or if they had genetic, medical, neurological, or neurodevelopmental conditions or significant hearing or vision impairments. All families gave written informed consent for participation and all study procedures were approved by the University of Minnesota’s Institutional Review Board (IRB) as well as Children’s MN IRB.

TABLE 1.

Descriptive data, N = 173

Variable N (%) M (SD) Range (scale range)
Infant age 12.10 (2.46) 8–18 months
Infant sex
 Female 89 (51%)
 Male 83 (48%)
Infant race
 Asian 3 (1.5%)
 Black/African/African-American 60 (35%)
 Indigenous American 3 (1.5%)
 Multiracial 38 (22%)
 White 62 (36%)
Infant ethnicity
 Hispanic/Latinx 29 (17%)
 Not Hispanic/Latinx 134 (77%)
Parent education
 High school 54 (32%)
 Some college 46 (27%)
 2-year degree 23 (13%)
 4-year degree/grad school 48 (28%)
Family income
 <$10,000 33 (19%)
 $10,001-$25,000 21 (12%)
 $25,001-$40,000 27 (16%)
 $40,001-$55,000 17 (10%)
 $55,001-$70,000 12 (7%)
 $70,001-$85,000 9 (5%)
 $85,001-$100,00 11 (6%)
 $100,001-$150,000 17 (10%)
 $150,001-$200,000 10 (6%)
 >$200,000 8 (5%)
Family percentage of FPL 253.88 (256.16) 13.14–1082.77
Parent depressive symptoms 10.86 (9.96) 0–49 (0–60)
Parent anxiety symptoms 3.40 (4.49) 0–19 (0–21)
Infant receptive language 21.70 (22.44) 0–89 (0–89)
Infant RJA mean score 2.73 (0.86) 0.38–4 (0–4)
Infant RJA coefficient of variation 0.18 (0.20) 0–1.15
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5.2 |. Measures

5.2.1 |. Demographics

Parents reported on their child’s age, sex, race, and ethnicity as part of a larger demographics survey. Parent education was self-reported categorically by the parent or guardian present at the well child visit (150 mothers, 14 fathers, 1 stepmother, 6 other) as the highest level of education completed. Responses were classified into four categories (Table 1): high school (including some high school, high school degree, and GED), some college, 2-year degree, and 4-year degree or graduate school (including 4-year degree, some grad school, Master’s degree, and doctoral or professional degree). Family percentage of the FPL was calculated continuously using parent self-reported family income and family size, with a value of 100% indicating a family living at the federal poverty line. Family income was collected categorically as ranges of incomes (Table 1). Percentage of the FPL (Table 1; M = 253.88, SD = 256.16, range = 13.14–1082.77) was calculated using the 2018 federal poverty guidelines and the median income in each range.

5.2.2 |. Parent depressive symptoms

Parent depressive symptoms were assessed using the Center for Epidemiological Studies–Depression Scale (CES-D; Radloff, 1977), which measures the frequency with which an individual experiences depressive symptomatology. Respondents were asked to report how often they experienced certain feelings over the past week, such as “I was happy” and “I felt that people disliked me.” This 20-item survey has a 4-point Likert scale ranging from ‘rarely or none of the time’ (0) to ‘all of the time’ (3). Cronbach’s alpha is 0.91.

5.2.3 |. Parent anxiety symptoms

Parent anxiety symptoms were assessed using the Generalized Anxiety Disorder–7 (GAD; Spitzer et al., 2006). Respondents were asked to report how often they were bothered by problems such as “trouble relaxing” and “feeling nervous, anxious, or on edge” over the past two weeks. This 7-item survey has a 4-point Likert scale ranging from ‘not at all’ (0) to ‘nearly every day’ (3). Cronbach’s alpha is 0.91.

5.2.4 |. Infant receptive language

Infant receptive language was assessed using the MacArthur Bates Communicative Development Inventories–Words and Gestures short form (MCDI; Fenson et al., 2000). This form assesses receptive language as parents report whether their child understands each word in a list of 89 words.

5.2.5 |. Response to joint attention (RJA)

Infant RJA was assessed using the Dimensional Joint Attention Assessment (DJAA; Elison et al., 2013), a floor task that assesses variability in infants’ abilities to respond to increasingly less redundant, more sophisticated RJA cues in a naturalistic play setting. During the assessment, one of two trained researchers sits on the floor with the infant and proceeds through 4 series of 4 hierarchically ordered RJA bids interspersed with play. The sequence begins with the least redundant bid (i.e., a gaze shift and head turn) and culminates with the most redundant bid (i.e., gaze shift, head turn, point, and vocalization; see Figure 1) until the infant responds or the sequence is completed. Each series is scored from 1 to 4 with a score of 4 denoting a response to the least redundant, most sophisticated cue.

FIGURE 1.

FIGURE 1

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Example DJAA bids. (a) First bid, experimenter shifts gaze and turns head. (b) Second bid, experimenter shifts gaze, turns head, and gives verbal cue. (c) Third bid, experimenter shifts gaze, turns head, and points. (d) Fourth bid, experimenter shifts gaze, turns head, points, and gives verbal cue

Dimensional Joint Attention Assessment mean scores were calculated for each infant as the mean of their 4 series scores to capture their average performance level. A higher mean score indicates greater ability to respond to less redundant, more sophisticated RJA cues. DJAA coefficients of variation were also calculated for each infant to capture the extent to which each infant responded consistently during the assessment. A lower coefficient of variation indicates greater response consistency, with a coefficient of variation of 0 indicating a consistent score across the 4 series.

5.3 |. Analytic approach

Forty-four participants (25%) were missing construct-level data in one or more of our variables of interest. Specifically, 13% were missing DJAA data, 11% were missing receptive language data, 8% were missing FPL, 2% were missing parent depressive and anxiety symptoms, 1% were missing infant age, and 1% were missing parent education. Given that we were able to predict missing data using our variables of interest (i.e., those with missing data were lower on family FPL (t(55) = −2.02, p = 0.04) and higher on parent anxiety (t(58) = 2.02, p = 0.05) and depressive symptoms (t(53) = 2.48, p = 0.01), it is likely that the data were missing at random (MAR) (i.e., the missing data patterns were associated with observed study variables), as opposed to missing completely at random (MCAR) in which the missing data are unrelated to observed study variables (Enders, 2010). Accordingly, to reduce the bias of model estimates and preserve statistical power, we employed multiple imputation techniques for the missing data. Multiple imputation was conducted using the MICE package for R (Buuren & Groothuis-Oudshoorn, 2011). A series of hierarchical linear regressions predicting infant DJAA mean scores and DJAA coefficient of variation were fit separately to the imputed datasets. Coefficient and model-level estimates were then pooled across the 10 imputed datasets using MICE to generate one average value. A sensitivity analysis was conducted with the non-imputed sample to confirm that the results of our analyses remained similar across both imputed and non-imputed datasets. All analyses were conducted using R (R Core Team, 2020). Linear models were fit using the lm function (R Core Team, 2020), which uses ordinary least squares estimation. Model fit was examined using R2 values and likelihood ratio tests.

6 |. RESULTS

We first established appropriate covariates and then fit a series of hierarchical linear regressions to test our hypotheses. Associations between covariates, hypothesized predictors, and infant mean DJAA and coefficient of variation are displayed in Table 2. Mean DJAA scores and coefficients of variation were modeled separately according to the following steps. First, we tested whether the covariates of infant age, infant sex, experimenter, and infant receptive language significantly predicted our outcome. Age (Table 3; t(141) = 7.48, p < 0.001) and receptive language (t(57) = 2.38, p = 0.02) significantly predicted mean DJAA scores and were retained in all future models of DJAA mean scores. Experimenter (t(95) = −2.64, p < 0.01) and infant age (t(110) = −2.73, p < 0.01) predicted DJAA coefficient of variation and were included in all subsequent models.

TABLE 2.

Correlations between RJA scores and hypothesized covariates and predictors

1 2 3 4 5 6 7
1. Infant age (months) —
2. Infant Mean DJAA 0.52*** —
3. Infant DJAA coefficient of variation −0.21* −0.50*** —
4. Infant Receptive Vocabulary 0.33*** 0.34*** −0.12 —
5. Family Percentage of the FPL 0.02 0.19* −0.07 −0.07 —
6. Parent Depressive Symptoms −0.03 −0.19* 0.13 −0.08 −0.27*** —
7. Parent Anxiety Symptoms −0.03 −0.15+ 0.14+ −0.14+ −0.10 0.76*** —
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+

p < .10,

*

p < .05,

**

p < .01,

***

p < .001

TABLE 3.

Unstandardized beta coefficients and standard errors for a taxonomy of linear models to predict mean RJA in 173 infants

Outcome: Infant Mean RJA
Model A Model B Model C Model D Model E
Infant Age 0.16*** (0.03) 0.16*** (0.03) 0.16*** (0.03) 0.17*** (0.03) 0.16*** (0.02)
Infant Receptive Language 0.007* (0.003) 0.008** (0.003) 0.007* (0.003) 0.008* (0.003) 0.008* (0.003)
FPL 0.0006** (0.0002) 0.0005 (0.0003) 0.0005 (0.0003)
Parent Education: some college 0.32+ (0.16) 0.29 (0.20) 0.28 (0.16)
Parent Education: 2-yr degree 0.34+ (0.20) 0.14 (0.20) 0.27 (0.20)
Parent Education: 4-year degree or graduate school 0.40* (0.16) 0.26 (0.16) 0.14 (0.20)
Parent depressive and anxiety symptoms −0.05 (0.03)
Constant 0.60+ (0.31) 0.46 (0.31) 0.36 (0.32) 0.31 (0.32) 0.34 (0.30)
R 2 0.29 0.32 0.33 0.35 0.36
Δ R 2 0.03 0.04 0.06 0.07
χ2 3.95* 1.47 1.29 1.41
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Note:: Parent education was included in the models as a factor with high school as the reference group. FPL was included as a continuous variable. Log likelihood test (χ2) compares each model to Model A.

+

p < .10,

*

p < .05,

**

p < .01,

***

p < .001.

Federal poverty level was then added to the models as a continuous variable, followed by a separate model with parent education entered as a factor, and finally, a third model with both FPL and parent education. FPL and parent education are associated (F = 45.05, p < 0.001) but there was low collinearity between FPL and parent education when modeled together in both the DJAA mean (VIF = 1.88) and coefficient of variation (VIF = 1.93) models. We then utilized likelihood ratio tests comparing model fit to the covariate-only models to determine whether to retain FPL or parent education.

Subsequently, parent depressive and anxiety symptom variables were added to models with the established covariates and SES variable(s). The majority of the parents in our sample demonstrated sub-clinical depressive and anxiety symptoms, with 23% and 11% of parents scoring at or above the established cut-off for clinical risk of depression (Lewinsohn et al., 1997) and anxiety (Spitzer et al., 2006), respectively. Because parent anxiety and depressive symptoms were highly correlated (r = 0.76) and collinear (VIFs = 2.66) when modeled together, these variables were combined into one parent depressive and anxiety symptoms variable by computing a sum of the z-scores prior to imputation. Residual plots of the best fitting models predicting mean DJAA and DJAA coefficient of variation were inspected for normality, homoscedasticity, and linearity and determined to meet assumptions.

6.1 |. Mean DJAA scores

Infant mean DJAA scores were normally distributed with a slightly higher mean (M = 2.7) than previous DJAA samples with this age range, but comparable variability (SD = 0.9; Stallworthy et al., in press). FPL significantly positively predicted infant mean RJA scores (t(131) = 2.42, p = 0.02) such that infants from families at a higher percentage of the FPL scored higher (Figure 2). Parent education significantly predicted infant mean RJA (t(117) = 2.30, p = 0.02) such that infants of parents who completed some college had higher RJA scores compared to infants of parents with a high school degree or less. Models fit with FPL or parent education explained a similar amount of the variance in infant mean RJA (Table 3), but only the model including FPL was significantly better fitting than the covariate model (p = 0.04). Adding to the model with the covariates and FPL, parent depressive and anxiety symptoms (t(103) = −1.41, p = 0.16) did not predict infant mean RJA.

FIGURE 2.

FIGURE 2

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Line graph of main effects model predicted infant mean RJA as a function of infant age and family percentage of the FPL, controlling for infant receptive vocabulary, and scatterplot of infant mean RJA adjusted for receptive vocabulary by infant age. FPL was modeled continuously but is plotted by sample quartiles for ease of viewing. Plot created using raw (non-imputed) data (N = 129)

6.2 |. DJAA coefficient of variation

The DJAA coefficient of variation (M = 0.18, SD = 0.20) for this sample was lower, on average, than previous DJAA samples (Stallworthy et al., in press). FPL did not predict RJA coefficient of variation (t(102) = −0.79, p = 0.42) nor did parent education (t(133) = −0.29, p = 0.77). Parent depressive and anxiety symptoms marginally predicted RJA coefficient of variation (t(72) = 1.73, p = 0.09) such that higher depressive and anxiety symptomology was associated with greater variation in RJA performance. Model comparisons suggest that the model including only covariates best fit the data.

7 |. DISCUSSION

Income inequality has increased in the United States over the past two decades (Pew Research Center, 2020), with a near doubling of the number of families living in deep poverty following the reform of welfare in 1996 (Edin & Shaefer, 2015). These structural socioeconomic inequities disproportionately impact families with young children, with 2.4 million infants and toddlers living below the federal poverty line in the U.S. in 2016 (Jiang & Koball, 2018). Within this context of national economic inequities, this study provides evidence that SES is positively associated with RJA, a foundational skill for social cognitive development that may contribute to the SES-related differences in later language and cognitive skills. The role of variation in the developmental timing of RJA is still uncertain and it is possible that there are multiple pathways (Cicchetti & Rogosch, 1996) to successful RJA development. Although this study was not designed to address mechanisms underlying the association between SES and infant RJA, we discuss our findings in the context of existing research on more proximal factors such as parenting behaviors, language experience, and aspects of the home environment.

We did not find evidence of an association between parent depressive and anxiety symptoms and infant RJA above and beyond the role of family SES. SES was negatively related to parent depressive and anxiety symptoms but those symptoms were not related to RJA controlling for SES, echoing other studies finding no relation between depressive symptoms and the frequency of parent-child engagement in joint attention (Gaffan et al., 2010; Goldsmith & Rogoff, 1997; Henderson & Donahue Jennings, 2003; Hwa-Froelich et al., 2008).

7.1 |. SES and RJA

Our findings suggest that infants’ emerging abilities to read RJA cues from adults may be sensitive to variation in home resource environments with potential developmental implications across domains. Income as a percentage of the FPL and parent education predicted variation in RJA abilities, such that higher income and education were associated with better RJA performance. However, when FPL and parent education were modeled together, neither predicted variation in RJA. These results suggest that maternal education and income are competing for the same variance in RJA abilities. It is likely that family income shapes infant RJA development indirectly and probabilistically by way of multiply interacting factors that are more proximal to the infant’s day-to-day experiences.

7.2 |. Parenting behavior

The increased daily stress experienced by parents living below the federal poverty level (Perkins et al., 2013) could constrain how parents interact with their children, but there is limited evidence of parenting behaviors as the mechanism underlying associations between SES and RJA. For example, past work suggests that parent scaffolding– including attention-directing behaviors and verbalizations– assists in fostering RJA in infants (Deák et al., 2008; Senju & Csibra, 2008). Other studies have found that joint attention during free-play is associated with mothers’ use of constructive verbal strategies and strategy support within a lower income sample (Hustedt & Raver, 2002). Moreover, mothers’ attentional maintenance, or following and reinforcing infant’s engagement with toys (Mendive et al., 2013; Tomasello & Farrar, 1986), is also associated with infant joint attention behaviors during free-play. In addition, maternal teaching behaviors at 6 months have been found to predict the amount of time spent in joint engagement at 9 months (Gaffan et al., 2010) and maintenance and vocalizations synchronized with their child’s activities are associated with 1-year gains in RJA abilities of children with autism spectrum disorder (Siller & Sigman, 2002). However, other studies have found no association between parent scaffolding behaviors, parent emotional availability, and infant RJA (Osório et al., 2011; Vaughan et al., 2003). Although prior literature describes associations between parent behaviors and infant joint attention, results from the current study suggest that factors thought to impact how parents interact with their children (i.e., anxiety and depression symptoms) did not appear to shape RJA cue-reading abilities.

7.3 |. Language

Response to joint attention development may share core requisites with emerging language abilities and its early course could be impacted by variation in early home language. Differences in home language exposure are known to influence infants’ language development (Hoff, 2003) and may also influence the sophistication with which they respond to RJA cues. Infants are more likely to respond to multimodal RJA cues from adults involving language bids (e.g., “Look at that”; e.g., Presmanes et al., 2007; Presmanes et al., 2007; Deák et al., 2008; Senju & Csibra, 2008) and RJA likely occurs within the choreography of more complex linguistic exchange during and other daily activities. Still, research on potential associations between home language exposure and infant joint attention is limited. One study found no association between either infant IJA or RJA and language exposure (i.e., monolingual or bilingual; Vaughan Van Heck et al., 2007). It is possible that SES-related differences in language exposure and the frequency of directed speech in the home (Hoff, 2003) could influence the sophistication with which infants respond to RJA cues. Specifically, higher educated mothers have been found to engage in lexically richer and more complex child-directed speech (Hoff, 2003). However, the association between family SES and infant RJA controlling for infant receptive language in this sample may indicate language exposure as an unlikely pathway between SES and RJA, given the documented associations between language exposure and child vocabulary (Hoff, 2003). Still, there may be aspects of the home language environment that shape cue-reading that are not accounted for by infant receptive language.

7.4 |. Home environment

Some posit that family income measures index overall resources in the home (Duncan & Magnuson, 2012). Fewer economic resources could influence RJA performance via characteristics of the home environments known to influence development such as cognitive stimulation (e.g., number of books and toys; Conger et al., 2010), household chaos (Evans et al., 2010), or stress levels (Johnson et al., 2016). Given that RJA often takes place to direct infants’ attention to a potentially novel or surprising object, fewer toys in the home might reduce the frequency of RJA bids from parents. Additionally, features such as chaos and a stressful atmosphere may preclude the frequency and effectiveness of the RJA bids that infants receive from the adults around them and their ability to learn from them. We are not aware of any empirical evidence linking these aspects of the home environment with infant RJA.

7.5 |. Strengths & Weaknesses

An important strength of this study is the use of the DJAA (Elison et al., 2013) which measures the sophistication of cues required to elicit a response and provides a novel social perspective on RJA abilities. The DJAA may be one reason why we found associations between SES and infant RJA where prior studies did not, as this assessment captures variability in the fine-grained social dimension of RJA performance in a naturalistic play setting whereas others measure more global RJA accuracy. The varied SES of the sample is another strength and afforded the opportunity to investigate relations between SES and infant RJA. Future studies modeling trajectories of RJA, SES, and possible mechanistic pathways across the first 5 years of life in a demographically varied sample would greatly contribute to our understanding. We also acknowledge the limitations of generalizing findings from this study to populations outside of the US where RJA cue-reading abilities may develop in accordance with different family, social, linguistic, and cultural structures.

8 |. CONCLUSION

Findings from this study demonstrate that resource-based differences in foundational social and cognitive abilities emerge in infancy. Additionally, findings shed light on the potential role of the home resource environment in shaping abilities to respond to increasingly less redundant, more sophisticated cues from others, implicating novel directions for future research. These findings underscore the importance of supporting families during the infant period and have implications for policies aimed at reducing the SES-related differences in academic achievement in the United States.

ACKNOWLEDGEMENTS

Special thanks to Bao Moua, Carolyn Lasch, Eli Johnson, Kirsten Dalrymple, patients, families, providers and medical staff at Children’s Minnesota without whom this research would not have been possible, supported by The JPB Foundation through a grant to The JPB Research Network on Toxic Stress: A Project of the Center on the Developing Child at Harvard University as well as a grant from the Bezos Family Foundation. The authors declare no conflicts of interest with regard to the funding source for this study.

Funding information

Bezos Family Foundation; JPB Foundation

APPENDIX A

TABLE A1.

DJAA scoring examples. If an infant looks to the experimenter’s pointing hand during the 3rd or 4th bid, but not the toy, they earn a score of 0.5.

graphic file with name nihms-1989282-t0001.jpg
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TABLE A2.

Infant RJA scores by SES categories, N = 173.

SES Mean DJAA DJAA coefficient of variation N Percentage
M (SD) M (SD)
Parent Education High school 2.47 (0.85) 0.19 (0.25) 54 31
Some college 2.74 (0.99) 0.17 (0.21) 46 27
2-year degree 2.94 (0.89) 0.15 (0.15) 23 13
4-year or graduate degree 2.95 (0.80) 0.18 (0.15) 48 28
Missing 2.25 0.56 2 1
FPL < 60 2.66 (0.95) 0.17 (0.20) 41 24
60–156 2.51 (0.82) 0.17 (0.18) 43 25
156–369 2.72 (0.92) 0.20 (0.23) 39 23
> 369 3.14 (0.82) 0.14 (0.16) 37 21
Missing 2.50 (0.74) 0.30 (0.26) 13 7
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APPENDIX B

FIGURE B1.

FIGURE B1

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Density plot of family FPL by categories of parent education (N = 160)

Footnotes

CONFLICTS OF INTEREST

No conflicts of interest to declare.

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