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Child Development

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Theories of Child Development and Their Impact on Early Childhood Education and Care

• Published: 29 October 2021
• Volume 51 , pages 15–30, ( 2023 )

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• Olivia N. Saracho   ORCID: orcid.org/0000-0003-4108-7790 1  

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Developmental theorists use their research to generate philosophies on children’s development. They organize and interpret data based on a scheme to develop their theory. A theory refers to a systematic statement of principles related to observed phenomena and their relationship to each other. A theory of child development looks at the children's growth and behavior and interprets it. It suggests elements in the child's genetic makeup and the environmental conditions that influence development and behavior and how these elements are related. Many developmental theories offer insights about how the performance of individuals is stimulated, sustained, directed, and encouraged. Psychologists have established several developmental theories. Many different competing theories exist, some dealing with only limited domains of development, and are continuously revised. This article describes the developmental theories and their founders who have had the greatest influence on the fields of child development, early childhood education, and care. The following sections discuss some influences on the individuals’ development, such as theories, theorists, theoretical conceptions, and specific principles. It focuses on five theories that have had the most impact: maturationist, constructivist, behavioral, psychoanalytic, and ecological. Each theory offers interpretations on the meaning of children's development and behavior. Although the theories are clustered collectively into schools of thought, they differ within each school.

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Saracho, O.N. Theories of Child Development and Their Impact on Early Childhood Education and Care. Early Childhood Educ J 51 , 15–30 (2023). https://doi.org/10.1007/s10643-021-01271-5

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DOI : https://doi.org/10.1007/s10643-021-01271-5

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Committee on the Science of Children Birth to Age 8: Deepening and Broadening the Foundation for Success; Board on Children, Youth, and Families; Institute of Medicine; National Research Council; Allen LR, Kelly BB, editors. Transforming the Workforce for Children Birth Through Age 8: A Unifying Foundation. Washington (DC): National Academies Press (US); 2015 Jul 23.

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4 Child Development and Early Learning

The domains of child development and early learning are discussed in different terms and categorized in different ways in the various fields and disciplines that are involved in research, practice, and policy related to children from birth through age 8. To organize the discussion in this report, the committee elected to use the approach and overarching terms depicted in Figure 4-1 . The committee does not intend to present this as a single best set of terms or a single best categorical organization. Indeed, it is essential to recognize that the domains shown in Figure 4-1 are not easily separable and that a case can be made for multiple different categorizations. For example, different disciplines and researchers have categorized different general cognitive processes under the categorical term “executive function.” General cognitive processes also relate to learning competencies such as persistence and engagement. Similarly, self-regulation has both cognitive and emotional dimensions. It is sometimes categorized as a part of executive function, as a part of socioemotional competence, or as a part of learning competencies. Attention and memory could be considered a part of general cognitive processes, as embedded within executive function, or linked to learning competencies related to persistence. Mental health is closely linked to socioemotional competence, but is also inseparable from health.

Report's organizational approach for the domains of child development and early learning.

The challenge of cleanly separating these concepts highlights a key attribute of all of these domains, which is that they do not develop or operate in isolation. Each enables and mutually supports learning and development in the others. Therefore, the importance of the interactions among the domains is emphasized throughout this chapter. For example, socioemotional competence is important for self-regulation, as are certain cognitive skills, and both emotional and cognitive self-regulation are important for children to be able to exercise learning competencies. Similarly, although certain skills and concept knowledge are distinct to developing proficiency in particular subject areas, learning in these subject areas also both requires and supports general cognitive skills such as reasoning and attention, as well as learning competencies and socioemotional competence. In an overarching example of interactions, a child's security both physically and in relationships creates the context in which learning is most achievable across all of the domains.

It is less important that all fields of research, practice, and policy adhere to the exact same categorizations, and more important that all conduct their work in a way that is cognizant and inclusive of all the elements that contribute to child development and early learning, and that all fields recognize that they are interactive and mutually reinforcing rather than hierarchical. This point foreshadows a theme that is addressed more fully in subsequent chapters. Because different fields and sectors may not use the same categorizations and vocabulary for these domains and skills, developing practices and policies that support more consistent and continuous development and early learning across birth through age 8 will require a concerted effort to communicate clearly and come to a mutual understanding of the goals for children. To communicate across fields and between research and practice communities requires being aware of the different categorical frameworks and terms that are used and being able to discuss the various concepts and content—and their implications—with clarity across those different frameworks. Practitioners and policy makers will be aided in achieving greater precision and clarity in their actions and decisions if those conducting and communicating future research keep this challenge in mind across domains, especially in those cases in which the taxonomy is most variable (e.g., self-regulation, executive function, general learning competencies).

With these caveats in mind, the remainder of this chapter addresses in turn the domains of child development and early learning depicted in Figure 4-1 : cognitive development, including learning of specific subjects; general learning competencies; socioemotional development; and physical development and health. The final section examines a key overarching issue: the effects on child development and early learning of the stress and adversity that is also an important theme in the discussion of the interaction between biology and environment in Chapter 3 .

• COGNITIVE DEVELOPMENT

This section highlights what is known about cognitive development in young children. It begins with key concepts from research viewpoints that have contributed to recent advances in understanding of the developing mind, and then presents the implications of this knowledge for early care and education settings. The following section addresses the learning of specific subjects, with a focus on language and mathematics.

Studies of early cognitive development have led researchers to understand the developing mind as astonishingly competent, active, and insightful from a very early age. For example, infants engage in an intuitive analysis of the statistical regularities in the speech sounds they hear en route to constructing language ( Saffran, 2003 ). Infants and toddlers derive implicit theories to explain the actions of objects and the behavior of people; these theories form the foundation for causal learning and more sophisticated understanding of the physical and social worlds. Infants and young children also are keenly responsive to what they can learn from the actions and words directed to them by other people. This capacity for joint attention may be the foundation that enables humans to benefit from culturally transmitted knowledge ( Tomasello et al., 2005 ). Infants respond to cues conveying the communicative intentions of an adult (such as eye contact and infant-directed speech) and tune in to what the adult is referring to and what can be learned about it. This “natural pedagogy” ( Csibra, 2010 ; Csibra and Gergely, 2009 ) becomes more sophisticated in the sensitivity of preschoolers to implicit pedagogical guides in adult speech directed to them ( Butler and Markman, 2012a , b , 2014 ). Young children rely so much on what they learn from others that they become astute, by the preschool years, in distinguishing adult speakers who are likely to provide them with reliable information from those who are not ( Harris, 2012 ; Jaswal, 2010 ; Koenig and Doebel, 2013 ). This connection of relationships and social interactions to cognitive development is consistent with how the brain develops and how the mind grows, and is a theme throughout this chapter.

Much of what current research shows is going on in young children's minds is not transparent in their behavior. Infants and young children may not show what they know because of competing demands on their attention, limitations in what they can do, and immature self-regulation. This is one of the reasons why developmental scientists use carefully designed experiments for elucidating what young children know and understand about the world. By designing research procedures that eliminate competing distractions and rely on simple responses (such as looking time and expressions of surprise), researchers seek to uncover cognitive processes that might otherwise be more difficult to see. Evidence derived in this experimental manner, such as the examples in the sections that follow, can be helpful in explaining young children's rapid growth in language learning, imitation, problem solving, and other skills.

Implicit Theories

One of the most important discoveries about the developing mind is how early and significantly very young children, even starting in infancy, are uniting disparate observations or discrete facts into coherent conceptual systems ( Carey, 2009 ; Gopnik and Wellman, 2012 ; Spelke and Kinzler, 2007 ). From very early on, children are not simply passive observers, registering the superficial appearance of things. Rather, they are building explanatory systems—implicit theories—that organize their knowledge. Such implicit theories contain causal principles and causal relations; these theories enable children to predict, explain, and reason about relevant phenomena and, in some cases, intervene to change them. As early as the first year of life, babies are developing incipient theories about how the world of people, other living things, objects, and numbers operates. It is important to point out that these foundational theories are not simply isolated forms of knowledge, but play a profound role in children's everyday lives and subsequent education.

One major example of an implicit theory that is already developing as early as infancy is “theory of mind,” which refers to the conceptual framework people use to reason about the mental lives of others as well as themselves. This example is discussed in detail below. Some additional illustrative examples of the development of implicit theories are provided in Box 4-1 .

Examples of the Development of Implicit Theories. Even babies hold some fundamental principles about how objects move about in space and time (Baillargeon et al., 2009). For example, babies are surprised (as measured by their increased looking time) if (more...)

Theory of Mind

People intuitively understand others' actions as motivated by desires, goals, feelings, intentions, thoughts, and other mental states, and we understand how these mental states affect one another (for example, an unfulfilled desire can evoke negative feelings and a motivation to continue trying to achieve the goal). One remarkable discovery of research on young children is that they are developing their own intuitive “map” of mental processes like these from very early in life ( Baillargeon et al., 2010 ; Saxe, 2013 ; Wellman and Woolley, 1990 ). Children's developing theory of mind transforms how they respond to people and what they learn from them. Infants and young children are beginning to understand what goes on in people's minds, and how others' feelings and thoughts are similar to and different from their own.

Infants first have a relatively simple theory of mind. They are aware of some basic characteristics: what people are looking at is a sign of what they are paying attention to; people act intentionally and are goal directed; people have positive and negative feelings in response to things around them; and people have different perceptions, goals, and feelings. Children add to this mental map as their awareness grows. From infancy on, developing theory of mind permeates everyday social interactions—affecting what and how children learn, how they react to and interact with other people, how they assess the fairness of an action, and how they evaluate themselves.

One-year-olds, for example, will look in their mother's direction when faced with someone or something unfamiliar to “read” mother's expression and determine whether this is a dangerous or benign unfamiliarity. Infants also detect when an adult makes eye contact, speaks in an infant-directed manner (such as using higher pitch and melodic intonations), and responds contingently to the infant's behavior. Under these circumstances, infants are especially attentive to what the adult says and does, thus devoting special attention to social situations in which the adult's intentions are likely to represent learning opportunities.

Other examples also illustrate how a developing theory of mind underlies children's emerging understanding of the intentions of others. Take imitation, for example. It is well established that babies and young children imitate the actions of others. Children as young as 14 to 18 months are often imitating not the literal observed action but the action they thought the actor intended—the goal or the rationale behind the action ( Gergely et al., 2002 ; Meltzoff, 1995 ). Word learning is another example in which babies' reasoning based on theory of mind plays a crucial role. By at least 15 months old, when babies hear an adult label an object, they take the speaker's intent into account by checking the speaker's focus of attention and deciding whether they think the adult indicated the object intentionally. Only when babies have evidence that the speaker intended to refer to a particular object with a label will they learn that word ( Baldwin, 1991 ; Baldwin and Moses, 2001 ; Baldwin and Tomasello, 1998 ).

Babies also can perceive the unfulfilled goals of others and intervene to help them; this is called “shared intentionality.” Babies as young as 14 months old who witness an adult struggling to reach for an object will interrupt their play to crawl over and hand the object to the adult ( Warneken and Tomasello, 2007 ). By the time they are 18 months old, shared intentionality enables toddlers to act helpfully in a variety of situations; for example, they pick up dropped objects for adults who indicate that they need assistance (but not for adults who dropped the object intentionally) ( Warneken and Tomasello, 2006 ). Developing an understanding of others' goals and preferences and how to facilitate them affects how young children interpret the behavior of people they observe and provides a basis for developing a sense of helpful versus undesirable human activity that is a foundation for later development of moral understanding (cf. Bloom, 2013 ; Hamlin et al., 2007 ; Thompson, 2012 , 2015 ).

Developing Implicit Theories: Implications for Adults

The research on the development of implicit theories in children has important implications for how adults work with and educate young children. Failure to recognize the extent to which they are construing information in terms of their lay theories can result in educational strategies that oversimplify material for children. Educational materials guided by the assumption that young children are “concrete” thinkers—that they cannot deal with abstraction or reason hypothetically—leads educators to focus on simple, descriptive activities that can deprive children of opportunities to advance their conceptual frameworks. Designing effective materials in a given domain or subject matter requires knowing what implicit theories children hold, what core causal principles they use, and what misconceptions and gaps in knowledge they have, and then using empirically validated steps to help lead them to a more accurate, more advanced conceptual framework.

Statistical Learning

Statistical learning refers to the range of ways in which children, even babies, are implicitly sensitive to the statistical regularities in their environment, although they are not explicitly learning or applying statistics. Like the development of implicit theories, this concept of statistical learning counters the possible misconception of babies as passive learners and bears on the vital importance of their having opportunities to observe and interact with the environment. Several examples of statistical learning are provided in Box 4-2 .

Examples of Statistical Learning. Infants can use information about the statistics of syllables in the speech they hear to help them parse words. How do we know from hearing prettybaby that baby is more likely to be a word than tyba ? One way is that the (more...)

Understanding Causal Inference

Children's intuitive understanding of causal inference has long been recognized as a fundamental component of conceptual development. Young children, although not explicitly or consciously experimenting with causality, can experience observations and learning that allow them to conclude that a particular variable X causes (or prevents) an effect Y. Recent advances in the field have documented the ways young children can implicitly use the statistics of how events covary to infer causal relations, make predictions, generate explanations, guide their exploration, and enable them to intervene in the environment. The understanding of causal inference also provides an example of how different cognitive abilities—such as a sensitivity to statistical regularities and the development of implicit theories based on observation and learning (discussed in the two preceding sections and Box 4-2 )—interact with and can mutually support each other. There is now a substantial literature on young children's implicit ability to use what they observe in different conditions to understand the relations between variables. Several examples of young children developing the ability to understand causal inference are provided in Box 4-3 .

Examples of Understanding Causal Inference. One of the first studies of children's understanding of causal inference showed that children can rule out one variable and isolate another (Gopnik et al., 2001). Preschool children were presented with a machine (more...)

Sensitivity to Teaching Cues

Csibra and Gergely (2009) argue that humans are equipped with a capacity to realize when someone is communicating something for their benefit and that they construe that information differently than when they merely witness it. As noted previously in the discussion of developing theory of mind, children as early as infancy devote special attention to social situations that are likely to represent learning opportunities because adults communicate that intention. Information learned in such communicative contexts is treated as more generalizable and robust than that learned in a noncommunicative context.

In one study, for example, 9-month-old babies saw an adult either reach for an object (a noncommunicative act) or point to an object (a communicative act). The entire display was then screened from view, and after a brief delay, the curtains were opened, and babies saw either the same object in a new location or a new object in the same location. The short delay imposed a memory requirement, and for babies this young, encoding both the location and the identity of the object taxes their memory. The location of the object will typically be more salient and memorable to babies than the object's properties, but the prediction of this study was that babies who saw the adult point to the object would construe the pointing as a communicative act—“this adult is showing me something”—and would thus be more likely to encode the properties as opposed to the location of the object. Babies' looking times served as a measure of their surprise at or interest in an unexpected event. As predicted, babies appeared to encode different aspects of the event in the different conditions. When they had previously witnessed the adult reaching for the object, they were surprised when the object was in a new location but showed no renewed interest when there was a different object in the old location. In contrast, when babies first saw an adult point to the object, they were surprised when a new object appeared in the old location but not when the old object had changed locations ( Yoon et al., 2008 ).

Infants' Sensitivity to Teaching Cues: Implications for Adults

Babies have the capacity to realize when someone is communicating something for their benefit and therefore to construe information differently than when they merely witness it. When adults use face-to-face contact, call a baby's name, and point for the baby's benefit, these signals lead babies to recognize that someone is teaching them something, and this awareness can affect how and what they learn.

The significance of eye contact and other communication cues also is evident in research on whether, how, and when young children learn from video and other forms of digital media. Experiments conducted with 24-month-olds, for example, revealed that they can learn from a person on a video screen if that person is communicating with them through a webcam-like environment, but they showed no evidence of learning from a prerecorded video of that person. The webcam environment included social cues, such as back-and-forth conversation and other forms of social contact that are not possible in prerecorded video. Other studies found that toddlers learned verbs better during Skype video chats than during prerecorded video chats that did not allow for authentic eye contact or back-and-forth interaction ( Roseberry et al., 2014 ; Troseth et al., 2006 ). (See also Chapter 6 for more on technology and learning.)

The benefits of communicative pedagogical contexts for the conceptual development of preschool children also have been investigated. In one set of studies, 4-year-old children were exposed to a novel object's function either by seeing an adult deliberately use the object or by seeing the adult deliberately use the object after maintaining eye contact with the child and saying “watch this.” In both conditions, children noticed the object's property and attempted to elicit it from other similar objects. But when those objects were doctored to be nonfunctional, the children in the nonpedagogical condition quickly abandoned their attempts to elicit the property and played with the objects in some other way. Children who saw the same evidence but with direct communication for their benefit persisted in trying to elicit the property from other objects ( Butler and Markman, 2012a , b ). In other words, children's conviction that other similar objects should have the same unforeseen property was bolstered by their belief that the adult was performing the function for their benefit. Moreover the intentional (but nonpedagogical) condition versus the pedagogical condition produced strikingly different conceptions of the function ( Butler and Markman, 2014 ). Four- and 5-year-old children witnessed an object's function and were then given a set of objects to play with. Some objects were identical in appearance to the first object, while some differed in color (in one study) or shape (in another). Half of the objects of each color (or shape) had the unforeseen property, and half did not. Children were told they could play with the objects for a while and then should put them away in their appropriate boxes when done. The goal was to see whether children would sort the objects by the salient perceptual property (color or shape) or by function. Children in the pedagogical condition viewed the function as definitive and classified the objects by systematically testing each to see whether it had the function, while children in the nonpedagogical condition sorted by the salient color or shape. Thus, identical evidence is construed differently when children believe it has been produced for their benefit.

Effects of Adult Language on Cognition

Understanding the power of language is important for people who interact with children. Simple labels can help children unify disparate-looking things into coherent categories; thus labeling is a powerful way to foster conceptual development. Labels also can reify categories or concepts in ways that may or may not be intended. For example, frequently hearing “boys and girls” line up for recess, quiet down, etc. implicitly reinforces gender as an important dimension, compared with saying “children.” Box 4-4 presents examples of linguistic distinctions that affect children's construction of conceptual systems.

Examples of the Effects of Adult Language on Cognition. Some kinds of categories—two round balls, for example—are fairly easy to form, such that even babies treat the objects as similar. But many objects that adults view as members of (more...)

Effects of Language Used by Adults on Children's Cognitive Development: Implications for Adults

Awareness of the benefits and pitfalls of the language used by adults is important for people who interact with children. The language used by adults affects cognitive growth and learning in children in many subtle ways. Labeling is a powerful way to foster conceptual development. Simple labels can help children unify disparate things into coherent categories, but can also have the unintended consequence of reinforcing categories or concepts that are not desirable.

Conclusions About Cognitive Development and Early Learning Learning begins prenatally, and children are not only “ready to learn” but already actively learning from the time they are born. From birth, children's minds are active and inquisitive, and early thinking is insightful and complex. Many of the foundations of sophisticated forms of learning, including those important to academic success, are established in the earliest years of life. Development and early learning can be supported continuously as a child develops, and early knowledge and skills inform and influence future learning. When adults understand how the mind develops, what progress children make in their cognitive abilities, and how active inquiry and learning are children's natural inclination, they can foster cognitive growth by supporting children's active engagement with new experiences and providing developmentally appropriate stimulation of new learning through responsive, secure, and sustained caregiving relationships.

Implications for Care and Education Settings and Practitioners

The research findings on cognitive development in young children summarized above reflect an evolving understanding of how the mind develops during the early years and should be part of the core knowledge that influences how care and education professionals support young children's learning, as discussed in Chapter 7 . Many of these concepts describe cognitive processes that are implicit. By contrast with the explicit knowledge that older children and adults can put into words, implicit knowledge is tacit or nonconscious understanding that cannot readily be consciously described (see, e.g., Mandler, 2004 ). Examples of implicit knowledge in very young children include many of the early achievements discussed above, such as their implicit theories of living things and of the human mind and their nonconscious awareness of the statistical frequency of the associations among speech sounds in the language they are hearing. Infants' and young children's “statistical learning” does not mean that they can count, nor are their “implicit theories” consciously worked out. Not all early learning is implicit, of course. Very young children are taking significant strides in their explicit knowledge of language, the functioning of objects, and the characteristics of people and animals in the world around them. Thus early learning occurs on two levels: the growth of knowledge that is visible and apparent, and the growth of implicit understanding that is sometimes more difficult to observe.

This distinction between implicit and explicit learning can be confusing to early childhood practitioners (and parents), who often do not observe or recognize evidence for the sophisticated implicit learning—or even the explicit learning—taking place in the young children in their care. Many of the astonishingly competent, active, and insightful things that research on early cognitive development shows are going on in young children's minds are not transparent in their behavior. Instead, toddlers and young children seem highly distractable, emotional, and not very capable of managing their impulses. All of these observations about young children are true, but at the same time, their astonishing growth in language skills, their very different ways of interacting with objects and living things, and their efforts to share attention (such as through pointing) or goals (such as through helping) with an adult suggest that the cognitive achievements demonstrated in experimental settings have relevance to their everyday behavior.

This point is especially important because the cognitive abilities of young children are so easily underestimated. In the past, for example, the prevalent belief that infants lack conceptual knowledge meant that parents and practitioners missed opportunities to explore with them cause and effect, number, or symbolic play. Similarly, the view that young children are egocentric caused many adults to conclude that there was little benefit to talking about people's feelings until children were older—this despite the fact that most people could see how attentive young children were to others' emotions and how curious about their causes.

In light of these observations, how do early educators contribute to the cognitive growth of children in their first 3 years? One way is by providing appropriate support for the learning that is occurring in these very young children (see, e.g., Copple et al., 2013 ). Using an abundance of child-directed language during social interaction, playing counting games (e.g., while stacking blocks), putting into words what a classroom pet can do or why somebody looks sad, exploring together what happens when objects collide, engaging in imitative play and categorization (sorting) games—these and other shared activities can be cognitively provocative as long as they remain within the young child's capacities for interest and attention. They also build on understandings that young children are implicitly developing related to language; number; object characteristics; and implicit theories of animate and inanimate objects, physical causality, and people's minds. The purpose of these and other activities is not just to provide young children with cognitive stimulation, but also to embed that stimulation in social interaction that provokes young children's interest, elicits their curiosity, and provides an emotional context that enables them to focus their thinking on new discoveries. The central and consistent feature of all these activities is the young child's shared activity with an adult who thoughtfully capitalizes on his or her interests to provoke cognitive growth. The implications for instructional practices and curricula for educators working with infants and toddlers are discussed further in Chapter 6 .

Another way that educators contribute to the cognitive growth of infants and toddlers is through the emotional support they provide ( Jamison et al., 2014 ). Emotional support is afforded by the educator's responsiveness to young children's interests and needs (including each child's individual temperament), the educator's development of warm relationships with children, and the educator's accessibility to help when young children are exploring on their own or interacting with other children ( Thompson, 2006 ). Emotional support of this kind is important not only as a positive accompaniment to the task of learning but also as an essential prerequisite to the cognitive and attentional engagement necessary for young children to benefit from learning opportunities. Because early capacities to self-regulate emotion are so limited, a young child's frustration or distress can easily derail cognitive engagement in new discoveries, and children can lose focus because their attentional self-regulatory skills are comparably limited. An educator's emotional support can help keep young children focused and persistent, and can also increase the likelihood that early learning experiences will yield successful outcomes. Moreover, the secure attachments that young children develop with educators contribute to an expectation of adult support that enables young children to approach learning opportunities more positively and confidently. Emotional support and socioemotional development are discussed further later in this chapter.

The characteristics of early learning call for specific curricular approaches and thoughtful professional learning for educators, but it is also true that less formal opportunities to stimulate early cognitive growth emerge naturally in children's everyday interactions with a responsive adult. Consider, for example, a parent or other caregiver interacting with a 1-year-old over a shape-sorting toy. As they together are choosing shapes of different colors and the child is placing them in the appropriate (or inappropriate) cutout in the bin, the adult can accompany this task with language that describes what they are doing and why, and narrates the child's experiences of puzzlement, experimentation, and accomplishment. The adult may also be using number words to count the blocks as they are deposited. The baby's attention is focused by the constellation of adult behavior—infant-directed language, eye contact, and responsiveness—that signals the adult's teaching, and this “pedagogical orientation” helps focus the young child's attention and involvement. The back-and-forth interaction of child and adult activity provides stimulus for the baby's developing awareness of the adult's thinking (e.g., she looks at each block before commenting on it or acting intentionally on it) and use of language (e.g., colors are identified for each block, and generic language is used to describe blocks in general). In this interaction, moreover, the baby is developing both expectations for what this adult is like—safe, positive, responsive—and skills for social interaction (such as turn taking). Although these qualities and the learning derived from them are natural accompaniments to child-focused responsive social interaction with an adult caregiver, the caregiver's awareness of the child's cognitive growth at this time contributes significantly to the adult's ability to intentionally support new discovery and learning.

As children further develop cognitively as preschoolers, their growth calls for both similar and different behavior by the adults who work with them. While the educator's emotional support and responsiveness remain important, children from age 3 to 5 years become different kinds of thinkers than they were as infants and toddlers ( NRC, 2001 ). First, they are more consciously aware of their knowledge—much more of their understanding is now explicit. This means they are more capable of deliberately enlisting what they know into new learning situations, although they are not yet as competent or strategic in doing so as they will be in the primary grades. When faced with a problem or asked a question, they are more capable of offering an answer based on what they know, even when their knowledge is limited. Second, preschoolers are more competent in learning from their deliberate efforts to do so, such as trial-and-error or informal experimentation. While their success in this regard pales by comparison with the more strategic efforts of a grade-schooler, their “let's find out” approach to new challenges reflects their greater behavioral and mental competence in figuring things out. Third, preschoolers also are intuitive and experiential, learning by doing rather than figuring things out “in the head.” This makes shared activities with educators and peers potent opportunities for cognitive growth.

Nonetheless, the potential to underestimate the cognitive abilities of young children persists in the preschool and kindergarten years. In one study, for example, children's actual performance was six to eight times what was estimated by their own preschool teachers and other experts in consulting, teacher education, educational research, and educational development ( Claessens et al., 2014 ; Van den Heuvel-Panhuizen, 1996 ). Such underestimation represents a lost opportunity that can hinder children's progress. A study in kindergarten revealed that teachers spent most of their time in basic content that children already knew, yet the children benefited more from advanced reading and mathematics content ( Claessens et al., 2014 )—an issue discussed in depth in Chapter 6 . Unfortunately, when care and education professionals underestimate children's abilities to understand and learn subject-matter content, the negative impact is greatest on those with the fewest prior learning experiences ( Bennett et al., 1984 ; Clements and Sarama, 2014 ).

Conversely, when educators practice in a way that is cognizant of the cognitive progress of children at this age, they can more deliberately enlist the preschool child's existing knowledge and skills into new learning situations. One example is interactive storybook reading, in which children describe the pictures and label their elements while the adult and child ask and answer questions of each other about the narrative. Language and literacy skills also are fostered at this age by the adult's use of varied vocabulary in interaction with the child, as well as by extending conversation on a single topic (rather than frequently switching topics), asking open-ended questions of the child, and initiating conversation related to the child's experiences and interests ( Dickinson, 2003 ; Dickinson and Porche, 2011 ; Dickinson and Tabors, 2001 ). In each case, dialogic conversation about text or experience draws on while also extending children's prior knowledge and language skills. Language and literacy skills are discussed further in a subsequent section of this chapter, as well as in Chapter 6 .

Another implication of these cognitive changes is that educators can engage preschool children's intentional activity in new learning opportunities. Children's interest in learning by doing is naturally suited to experimental inquiry related to science or other kinds of inquiry-based learning involving hypothesis and testing, especially in light of the implicit theories of living things and physical causality that children bring to such inquiry ( Samarapungavan et al., 2011 ). In a similar manner, board games can provide a basis for learning and extending number concepts. In several experimental demonstrations, when preschool children played number board games specifically designed to foster their mental representations of numerical quantities, they showed improvements in number line estimates, count-on skill, numerical identification, and other important quantitative concepts ( Laski and Siegler, 2014 ).

Other research has shown that instructional strategies that promote higher-level thinking, creativity, and even abstract understanding, such as talking about ideas or about future events, is associated with greater cognitive achievement by preschool-age children (e.g., Diamond et al., 2013 ; Mashburn et al., 2008 ). For example, when educators point out how cardinal numbers can be used to describe diverse sets of elements (four blocks, four children, 4 o'clock), it helps them generalize an abstract concept (“fourness”) that describes a set rather than the characteristics of each element alone. These activities also can be integrated into other instructional practices during a typical day.

Another implication of the changes in young children's thinking during the preschool years concerns the motivational features of early learning. Preschool-age children are developing a sense of themselves and their competencies, including their academic skills ( Marsh et al., 1998 , 2002 ). Their beliefs about their abilities in reading, counting, vocabulary, number games, and other academic competencies derive from several sources, including spontaneous social comparison with other children and feedback from teachers (and parents) concerning their achievement and the reasons they have done well or poorly. These beliefs influence, in turn, children's self-confidence, persistence, intrinsic motivation to succeed, and other characteristics that may be described as learning skills (and are discussed more extensively later in this chapter). Consequently, how teachers provide performance feedback to young children and support for their self-confidence in learning situations also is an important predictor of children's academic success ( Hamre, 2014 ).

In the early elementary years, children's cognitive processes develop further, which accordingly influences the strategies for educators in early elementary classrooms. Primary grade children are using more complex vocabulary and grammar. They are growing in their ability to make mental representations, but they still have difficulty grasping abstract concepts without the aid of real-life references and materials ( Tomlinson, 2014 ). This is a critical time for children to develop confidence in all areas of life. Children at this age show more independence from parents and family, while friendship, being liked and accepted by peers, becomes more important. Being in school most of the day means greater contact with a larger world, and children begin to develop a greater understanding of their place in that world ( CDC, 2014 ).

Children's growing ability to self-regulate their emotions also is evident in this period (discussed more extensively later in this chapter). Children understand their own feelings more and more, and learn better ways to describe experiences and express thoughts and feelings. They better understand the consequences of their actions, and their focus on concern for others grows. They are very observant, are willing to play cooperatively and work in teams, and can resolve some conflicts without seeking adult intervention ( CDC, 2014 ). Children also come to understand that they can affect others' perception of their emotions by changing their affective displays ( Aloise-Young, 1993 ). Children who are unable to self-regulate have emotional difficulties that may interfere with their learning. Just as with younger children, significant adults in a child's life can help the child learn to self-regulate ( Tomlinson, 2014 ).

Children's increasing self-regulation means they have a greater ability to follow instructions independently in a manner that would not be true of preschool or younger children. Educators can rely on the growing cognitive abilities in elementary school children in using instructional approaches that depend more independently on children's own discoveries, their use of alternative inquiry strategies, and their greater persistence in problem solving. Educators in these settings are scaffolding the skills that began to develop earlier, so that children are able to gradually apply those skills with less and less external support. This serves as a bridge to succeeding in upper primary grades, so if students lack necessary knowledge and skills in any domain of development and learning, their experience during the early elementary grades is crucial in helping them gain those competencies.

Building on many of the themes that have emerged from this discussion, the following sections continue by looking in more depth at cognitive development with respect to learning specific subjects and then at other major elements of development, including general learning competencies, socioemotional development, and physical development and health.

• LEARNING SPECIFIC SUBJECTS

Interrelationships among different kinds of skills and abilities contribute to young children's acquisition of content knowledge and competencies, which form a foundation for later academic success. These skills and abilities include the general cognitive development discussed above, the general learning competencies that allow children to control their own attention and thinking; and the emotion regulation that allows children to control their own emotions and participate in classroom activities in a productive way (the latter two are discussed in sections later in this chapter). Still another important category of skills and abilities, the focus of this section, is subject-matter content knowledge and skills, such as competencies needed specifically for learning language and literacy or mathematics.

Content knowledge and skills are acquired through a developmental process. As children learn about a topic, they progress through increasingly sophisticated levels of thinking with accompanying cognitive components. These developmental learning paths can be used as the core of a learning trajectory through which students can be supported by educators who understand both the content and those levels of thinking. Each learning trajectory has three parts: a goal (to develop a certain competence in a topic), a developmental progression (children constructing each level of thinking in turn), and instructional activities (tasks and teaching practices designed to enable thinking at each higher level). Learning trajectories also promote the learning of skills and concepts together—an effective approach that leads to both mastery and more fluent, flexible use of skills, as well as to superior conceptual understanding ( Fuson and Kwon, 1992 ; National Mathematics Advisory Panel, 2008 ). See Chapter 6 for additional discussion of using learning trajectories and other instructional practices.

Every subject area requires specific content knowledge and skills that are acquired through developmental learning processes. It is not possible to cover the specifics here for every subject area a young child learns. To maintain a feasible scope, this chapter covers two core subject areas: (1) language and literacy and (2) mathematics. This scope is not meant to imply that learning in other areas, such as science, engineering, social studies, or the arts, is unimportant or less subject specific. Rather, these two were selected because they are foundational for other subject areas and for later academic achievement, and because how they are learned has been well studied in young children compared with many other subject areas.

Language and Literacy

Children's language development and literacy development are central to each other. The development of language and literacy includes knowledge and skills in such areas as vocabulary, syntax, grammar, phonological awareness, writing, reading, comprehension, and discourse skills. The following sections address the development of language and literacy skills, including the relationship between the two; the role of the language-learning environment; socioeconomic disparities in early language environments; and language and literacy development in dual language learners.

Development of Oral Language Skills

Language skills build in a developmental progression over time as children increase their vocabulary, average sentence length, complexity and sophistication of sentence structure and grammar, and ability to express new ideas through words ( Kipping et al., 2012 ). Catts and Kamhi (1999) define five features of language that both work independently and interact as children develop language skills: phonology (speech sounds of language), semantics (meanings of words and phrases), morphology (meaningful parts of words and word tenses), syntax (rules for combining and ordering words in phrases), and pragmatics (appropriate use of language in context). The first three parameters combined (phonology, semantics, and morphology) enable listening and speaking vocabulary to develop, and they also contribute to the ability to read individual words. All five features of language contribute to the ability to understand sentences, whether heard or read (O' Connor, 2014 ). Thus, while children's development of listening and speaking abilities are important in their own right, oral language development also contributes to reading skills.

Developing oral communication skills are closely linked to the interactions and social bonds between adults and children. As discussed earlier in this chapter, parents' and caregivers' talk with infants stimulates—and affects—language comprehension long before children utter their first words. This comprehension begins with pragmatics—the social aspects of language that include facial and body language as well as words, such that infants recognize positive (and negative) interactions. Semantics (understanding meanings of words and clusters of words that are related) soon follows, in which toddlers link objects and their attributes to words. Between the ages of 2 and 4, most children show dramatic growth in language, particularly in understanding the meanings of words, their interrelationships, and grammatical forms ( Scarborough, 2001 ).

Karmiloff and Karmiloff-Smith (2001) suggest that children build webs among words with similar semantics, which leads to broader generalizations among classes of related words. When adults are responsive to children's questions and new experiences, children expand their knowledge of words and the relationships among them. Then, as new words arise from conversation, storytelling, and book reading, these words are linked to existing webs to further expand the store of words children understand through receptive language and use in their own conversation. The more often adults use particular words in conversation with young children, the sooner children will use those words in their own speech ( Karmiloff and Karmiloff-Smith, 2001 ). Research has linked the size of vocabulary of 2-year-olds to their reading comprehension through fifth grade ( Lee, 2011 ).

One of the best-documented methods for improving children's vocabularies is interactive storybook reading between children and their caregivers (O' Connor, 2014 ). Conversations as stories are read improve children's vocabulary ( Hindman et al., 2008 ; Weizman and Snow, 2001 ), especially when children are encouraged to build on the possibilities of storybooks by following their interests ( Whitehurst et al., 1988 ; Zucker et al., 2013 ). Book reading stimulates conversation outside the immediate context—for example, children ask questions about the illustrations that may or may not be central to the story. This introduces new words, which children attach to the features of the illustrations they point out and incorporate into book-centered conversations. This type of language, removed from the here and now, is decontextualized language. Children exposed to experiences not occurring in their immediate environment are more likely to understand and use decontextualized language ( Hindman et al., 2008 ). Repeated routines also contribute to language development. As books are read repeatedly, children become familiar with the vocabulary of the story and their conversations can be elaborated. Routines help children with developmental delays acquire language and use it more intelligibly ( van Kleek, 2004 ).

Conversation around a story's content and emphasis on specific words in the text (i.e., the phonological and print features of words alongside their meanings) have long-term effects ( Zucker et al., 2013 ). The quality of adult readers' interactions with children appears to be especially important to children's vocabulary growth (see also Coyne et al., 2009 ; Justice et al., 2005 ). In a study with preschool children, Zucker and colleagues (2013) found that teachers' intentional talk during reading had a longer-lasting effect on the children's language skills than the frequency of the teachers' reading to the children. Moreover, the effect of the teachers' talk during reading was not moderated by the children's initial vocabulary or literacy abilities. The long-term effect of high-quality teacher–child book-centered interactions in preschool lasted through the end of first grade.

New research shows that the effects of interactive reading also hold when adapted to the use of digital media as a platform for decontextualized language and other forms of language development. A study of videobooks showed that when adults were trained to use dialogic questioning techniques with the videos, 3-year-olds learned new words and recalled the books' storylines ( Strouse et al., 2013 ). However, a few studies of e-books also have shown that the bells and whistles of the devices can get in the way of those back-and-forth conversations if the readers and the e-book designers are not intentional about using the e-books to develop content knowledge and language skills ( Parish-Morris et al., 2013 ). (See also the discussion of effective use of technology in instruction in Chapter 6 .)

Alongside developing depth of vocabulary (including the meaning of words and phrases and their appropriate use in context), other important parameters of language development are syntax (rules for combining and ordering words in phrases, as in rules of grammar) and morphology (meaningful parts of words and word tenses). Even before the age of 2, toddlers parse a speech stream into grammatical units ( Hawthorne and Gerken, 2014 ). Long before preschool, most children join words together into sentences and begin to use the rules of grammar (i.e., syntax) to change the forms of words (e.g., adding s for plurals or ed for past tense). Along with these morphemic changes to words, understanding syntax helps children order the words and phrases in their sentences to convey and to change meaning. Before children learn to read, the rules of syntax help them derive meaning from what they hear and convey meaning through speech. Cunningham and Zibulsky (2014 , p. 45) describe syntactic development as “the ability to understand the structure of a sentence, including its tense, subject, and object.”

Although syntactic understanding develops for most children through conversation with adults and older children, children also use these rules of syntax to extract meaning from printed words. This becomes an important reading skill after first grade, when text meaning is less likely to be supported with pictures. Construction of sentences with passive voice and other complex, decontextualized word forms are more likely to be found in books and stories than in directive conversations with young children. An experimental study illustrates the role of exposure to syntactic structures in the development of language comprehension ( Vasilyeva et al., 2006 ). Four-year-olds listened to stories in active or passive voice. After listening to ten stories, their understanding of passages containing these syntactic structures was assessed. Although students in both groups understood and could use active voice (similar to routine conversation), those who listened to stories with passive voice scored higher on comprehension of this structure.

Children's understanding of morphology—the meaningful parts of words—begins in preschool for most children, as they recognize and use inflected endings to represent verb tense (e.g., -ing, -ed, -s) and plurals, and continues in the primary grades as children understand and use prefixes and suffixes. By second and third grade, children's use of morphemes predicts their reading comprehension ( Nagy et al., 2006 ; Nunes et al., 2012 ).

Development of Literacy Skills

Literacy skills follow a developmental trajectory such that early skills and stages lead into more complex and integrated skills and stages ( Adams, 1990 ). For example, phonemic awareness is necessary for decoding printed words ( Ball and Blachman, 1991 ; Bradley and Bryant, 1983 ; O'Connor et al., 1995 ), but it is not sufficient. Students need to understand the alphabetic principle (that speech sounds can be represented by letters of the alphabet, which is how speech is captured in print) before they can use their phonemic awareness (the ability to hear and manipulate sounds in spoken words) to independently decode words they have never seen before ( Byrne and Fielding-Barnsley, 1989 ; O'Connor and >Jenkins, 1995 ). Thus, instruction that combines skill development for 4- to 6-year-old children in phonemic awareness, letter knowledge, and conceptual understanding and use of these skills is more effective than teaching the skills in isolation ( Byrne and Fielding-Barnsley, 1989 ; O'Connor and Jenkins, 1995 ).

Seminal theories and studies of reading describe an inextricable link between language development and reading achievement (e.g., Byrne and Fielding-Barnsley, 1995 ; Gough and Tunmer, 1986 ; Hoover and Gough, 1990 ; Johnston and Kirby, 2006 ; Joshi and Aaron, 2000 ; Tunmer and Hoover, 1993 ; Vellutino et al., 2007 ). Early oral language competencies predict later literacy ( Pearson and Hiebert, 2010 ). Not only do young children with stronger oral language competencies acquire new language skills faster than students with poorly developed oral language competencies ( Dickinson and Porche, 2011 ), but they also learn key literacy skills faster, such as phonemic awareness and understanding of the alphabetic principle ( Cooper et al., 2002 ). Both of these literacy skills in turn facilitate learning to read in kindergarten and first grade. By preschool and kindergarten listening and speaking abilities have long-term impacts on children's reading and writing abilities in third through fifth grade ( Lee, 2011 ; Nation and Snowling, 1999 ; Sénéchal et al., 2006 ).

Vocabulary development (a complex and integrative feature of language that grows continuously) and reading words (a skill that most children master by third or fourth grade) ( Ehri, 2005 ) are reciprocally related, and both reading words accurately and understanding what words mean contribute to reading comprehension ( Gough et al., 1996 ). Because comprehending and learning from text depend largely upon a deep understanding of the language used to communicate the ideas and concepts expressed, oral language skills (i.e., vocabulary, syntax, listening comprehension) are at the core of this relationship between language and reading ( NICHD Early Child Care Research Network, 2005 ; Perfetti, 1985 ; Perfetti and Hart, 2002 ). For example, children with larger speaking vocabularies in preschool may have an easier time with phoneme awareness and the alphabetic principle because they can draw on more words to explore the similarities among the sounds they hear in spoken words and the letters that form the words ( Metsala and Walley, 1998 ). Each word a child knows can influence how well she or he understands a sentence that uses that word, which in turn can influence the acquisition of knowledge and the ability to learn new words. A stronger speaking and listening vocabulary provides a deeper and wider field of words students can attempt to match to printed words. Being bogged down by figuring out what a given word means slows the rate of information processing and limits what is learned from a sentence. Thus, differences in early vocabulary can have cascading, cumulative effects ( Fernald et al., 2013 ; Huttenlocher, 1998 ). The transition from speaking and listening to reading and writing is not a smooth one for many children. Although a well-developed vocabulary can make that transition easier, many children also have difficulty learning the production and meanings of words. Longitudinal studies of reading disability have found that 70 percent of poor readers had a history of language difficulties ( Catts et al., 1999 ).

Conclusion About the Development of Language and Literacy Skills The oral language and vocabulary children learn through interactions with parents, siblings, and caregivers and through high-quality interactions with educators provide the foundation for later literacy and for learning across all subject areas, as well as for their socioemotional well-being. The language interactions children experience at home and in school influence their developing minds and their understanding of concepts and ideas.

Role of the Language-Learning Environment

Today's science of reading development focuses more broadly than on teaching children to read the actual words on a page. As stressed throughout this report, young children's development entails a back-and-forth process of social interactions with knowledgeable others in their environment ( Bruner, 1978 ; NRC and IOM, 2000 ; Vygotsky, 1978 , 1986 ), and research has focused on the language of these interactions, examining how children's linguistic experiences influence aspects of their development over time, including their literacy development. The daily talk to which children are exposed and in which they participate is essential for developing their minds—a key ingredient for building their knowledge of the world and their understanding of concepts and ideas. In turn, this conceptual knowledge is a cornerstone of reading success.

The bulk of the research on early linguistic experiences has investigated language input in the home environment, demonstrating the features of caregivers' (usually the mother's) speech that promote language development among young children. The evidence accumulated emphasizes the importance of the quantity of communicative input (i.e., the number of words and sentences spoken) as well as the quality of that input, as measured by the variety of words and syntactic structures used (for relevant reviews, see Rowe, 2012 ; Vasilyeva and Waterfall, 2011 ). Because children's language development is sensitive to these inputs, variability in children's language-based interactions in the home environment explains some of the variance in their language development.

A smaller but growing and compelling research base is focused on how children's literacy skills are influenced by language use in early care and education settings and schools—for example, linguistic features of these settings or elementary school teachers' speech and its relationship to children's reading outcomes ( Greenwood et al., 2011 ). This research has particularly relevant implications for educational practices (discussed further in Chapter 6 ).

The language environment of the classroom can function as a support for developing the kind of language that is characteristic of the school curriculum—for example, giving children opportunities to develop the sophisticated vocabulary and complex syntax found in texts, beginning at a very early age ( Schleppegrell, 2003 ; Snow and Uccelli, 2009 ). Moreover, advances in cognitive science suggest that it is not enough to be immersed in environments that offer multiple opportunities for exposure to varied and rich language experiences. Rather, the process also needs to be socially mediated through more knowledgeable persons who can impart their knowledge to the learner; again, social interaction is a critical component of cognitive development and learning. Early childhood settings and elementary classrooms thus not only present opportunities for exposure to varied language- and literacy-rich activities (whether written or spoken), but also provide a person who is expert in mediating the learning process—the educator.

Research demonstrates that teachers' use of high-quality language is linked to individual differences in language and literacy skills; this work likewise shows the substantial variation in the quality of teacher talk in early childhood classrooms (e.g., Bowers and Vasilyeva, 2011 ; Gámez and Levine, 2013 ; Greenwood et al., 2011 ; Huttenlocher et al., 2002 ). For example, Huttenlocher and colleagues (2002) found greater syntactic skills in preschoolers exposed to teachers who used more syntactically complex utterances. Another study found for monolingual English-speaking children that fourth-grade reading comprehension levels were predicted by exposure to sophisticated vocabulary in preschool. These effects were mediated by children's vocabulary and literacy skills in kindergarten ( Dickinson and Porche, 2011 ).

In classroom studies focused on the linguistic environment, the level of analysis has involved broad measures of language use, such as amount of talk (i.e., teacher–student interactions by minute: Connor et al., 2006 ), amount of instruction (i.e., in teacher-managed versus child-managed instruction: Connor et al., 2007 ), type of interaction style (i.e., didactic versus cognitively demanding talk or the amount of extended discourse: Dickinson and Smith, 1991 ; Jacoby and Lesaux, 2014 ; Smith and Dickinson, 1994 ), or instructional moves made by the teacher (e.g., modeling: see review in Lawrence and Snow, 2011 ). A commonly included measurement that has been linked to children's literacy development is extended discourse, defined as talk that “requires participants to develop understandings beyond the here and now and that requires the use of several utterances or turns to build a linguistic structure, such as in explanations, narratives, or pretend” ( Snow et al., 2001 , p. 2). Children are better prepared to comprehend narrative texts they encounter in school if their early language environments provide more exposure to and opportunities to participate in extended discourse. This is because extended discourse and narrative texts share similar patterns for communicating ideas ( Uccelli et al., 2006 ).

Engaging groups of children in effective extended discourse involves asking and discussing open-ended questions and encouraging turn taking, as well as monitoring the group to involve nonparticipating children ( Girolametto and Weitzman, 2002 ). In addition to using interactive storybook and text reading as a platform for back-and-forth conversations (often referred to as interactive or dialogic reading, as described in the preceding section) ( Mol et al., 2009 ; Zucker et al., 2013 ), engaging children in extended discourse throughout classroom activities (e.g., small-group learning activities, transitions and routines [ van Kleek, 2004 ], dramatic play [ Mages, 2008 ; Morrow and Schickedanz, 2006 ]) is fundamental to providing a high-quality language-learning environment ( Jacoby and Lesaux, 2014 ).

In an example of the influence of the quantity and quality of teachers' language input in linguistically diverse classrooms, Bowers and Vasilyeva (2011) found that the total number of words produced by teachers and the diversity of their speech (which was entirely in English) were related to vocabulary gains for children from both English-only households and households in which English was not the primary language, respectively. Thus, they found that preschool dual language learners benefited only from increased quantities of language exposure and showed a negative relationship between vocabulary growth and teachers' syntactic complexity. By contrast, the English-only children—who presumably had more developed English language proficiency skills—benefited from the diversity of teachers' vocabulary and syntactic complexity. These findings are consistent with the notion that to promote language learning, different inputs are needed at different developmental stages ( Dickinson and Freiberg, 2009 ; Gámez and Lesaux, 2012 ). Children benefit from hearing simplified speech during very early word learning ( Furrow et al., 1979 ). With more exposure to language and more advanced vocabulary development, they benefit from speech input that is more complex (i.e., Hoff and Naigles, 2002 ). Hoff (2006) suggests that if input is too complex, children filter it out without negative consequences—as long as sufficient beneficial input is available to them. On the other hand, “children have no way to make up for input that is too simple” ( Hoff, 2006 , p. 75).

An important consideration in light of these findings is that recent research in early childhood classrooms serving children from low-income backgrounds suggests that daily high-quality language-building experiences may be rare for these children. For example, in a Head Start organization serving large numbers of Latino children a recent observational study found a preschool environment lacking in the frequent and high-quality teacher–child language interactions that are needed to support language and literacy development ( Jacoby and Lesaux, 2014 ). Literacy instruction was highly routine based and with low-level language structures. Extended discourse was infrequently used; only 22 percent of observed literacy-based lessons included at least one instance of extended discourse between a teacher and a child or group of children. Instead, teachers asked questions that yielded short answers or linked only to the here and now (e.g., What day is it today? What is the weather today? ). These features of infrequent extended discourse and predominantly routine-based literacy instruction were remarkably stable across teachers and classrooms. Other research investigating teacher talk in Head Start preschool classrooms has produced similar findings (e.g., Dickinson et al., 2008 ).

This is consistent with findings that there are sizable cultural and socioeconomic differences in high-quality language-promoting experiences in the home and in the classroom environment in early childhood ( Dickinson, 2003 ; Dickinson and Porche, 2011 ; Dickinson and Tabors, 2001 ; Raikes et al., 2006 ), just as such differences have been found in the number of words children hear by the time they enter school ( Bradley and Corwyn, 2002 ; Fernald et al., 2013 ; Hart and Risley, 1995 ; Schneidman et al., 2013 ; Weisleder and Fernald, 2013 ). At the same time, for children from low-resource backgrounds oral language skills show an even stronger connection to later academic outcomes than for children from high-resource backgrounds. Given these findings, rich linguistic experiences at early ages may therefore be especially important for these children. Even small improvements in the literacy environment can have especially strong effects for children who are raised in low-income households ( Dearing et al., 2001 ; Dickinson and Porche, 2011 ).

In sum, the language environment has important effects on children's learning, and children benefit from extensive opportunities to listen to and use complex spoken language ( National Early Literacy Panel, 2008 ). Teachers' use of high-quality language is linked to individual differences in language and literacy skills, and there is considerable variation in the quantity and quality of teachers' language use across classrooms. The quality of the classroom language environment is a lever for lasting improvements in children's language and literacy development, and it is important to tailor classroom talk to match the developmental stage of children's language acquisition.

Creating a Rich Language Environment: Implications for Adults

Improving language environments for young children requires daily learning opportunities that focus on the diversity and complexity of language used with young children. Practically speaking, this can be achieved through extended discourse, with multiple exchanges or turns that go beyond the immediate “here and now” using explanations, narratives, or pretend. Extended discourse can take place throughout all activities and in specific interactions, especially using book reading as a platform for back-and-forth conversations.

Further research is needed to advance understanding of language-based classroom processes and how dynamic and ongoing interactions facilitate or impede children's literacy. Such studies could advance existing research in at least two ways. In particular, it could further elucidate how language-based social processes in the classroom affect literacy development for the many students who enter schools and other care and education settings with limited proficiency in English. The majority of published studies focused on language-based interactions are focused on English-only learners, despite the fact that social processes can be experienced differently by different groups, even within the same setting ( Rogoff and Angelillo, 2002 ; Tseng and Seidman, 2007 ). Gámez and Levine (2013) suggest that future research examine the influence of dual-language input on dual language learners' language development; the nature of teacher talk during different parts of the instructional day, including joint book reading, and how these language experiences predict dual language learners' language skills; and the impact of classroom talk interventions—those that aim to manipulate the frequency and complexity of teachers' language—on both the language environment and dual language learners' language development.

In addition, prior research has measured a two-way process in a largely unidirectional manner—measuring speech only from parent to child or educator to student. It would be more valuable going forward if research were guided by the notion that the language-based interactions between students and educators mediate instruction, and were therefore to explore how communicative feedback loops, both adult–child and child–peer interactions, influence children's learning and development. Taking into account the student's contribution to the classroom language environment is particularly important in light of evidence that teachers modify their speech to conform to their students' limited language proficiency levels, potentially leading to a lower-quality language environment that impedes students' language growth ( Ellis, 2008 ; see Huttenlocher et al., 2010 ; Justice et al., 2013 ). More specifically, Justice and colleagues (2013) suggest that future research examine teacher–child language interactions in a multidimensional way to explore how syntactic complexity, cognitive demand, and even linguistic form (e.g., questions, comments) relate to each other; the links between children's use of complex syntax in classroom-based interactions and their future general language ability; and interventions designed to enhance classroom language interactions, focusing on both proximal and distal outcomes for children. Finally, greater understanding is needed of the ways in which the classroom language processes described in this section might act as a foundational mediator of the efficacy of interventions focused on learning outcomes in other domains and subject areas.

Alongside student–educator interactions, studies show that peer-to-peer interactions in the classroom may also have positive impacts on children's vocabulary and expressive language abilities. Children spend a significant amount of time interacting with other children in classroom settings, and a 2009 study examining the language growth and abilities of 4-year-olds in prekindergarten classrooms found that peers who have higher language abilities positively affect other children's language development. This study also found that children with advanced language skills will receive greater benefits from interacting with peers who also have advanced language skills ( Mashburn et al., 2009 ). These findings are similar to another study showing that peer interactions in the classroom, along with the ability level of the peers, have positive effects on the child's cognitive, prereading, expressive language skills ( Henry and Rickman, 2007 ). In order to achieve these benefits, however, the preschool classrooms need to be designed so that peers can interact with one another, and include activities such as reading books and engaging in play together. Children with teachers who organize the day with optimal amounts of time for peer-to-peer interactions may achieve greater language growth ( Mashburn et al., 2009 ).

Language and Literacy Development in Dual Language Learners 1

For children whose home language is not the predominant language of their school, educators and schools need to ensure the development of English proficiency. Both parents and preschool teachers can be particularly useful in improving these children's depth of vocabulary ( Aukrust, 2007 ; Roberts, 2008 ). At the same time, children can be helped to both build and maintain their first language while adding language and literacy skills in English ( Espinosa, 2005 ). In support of this as a long-term goal are the potential advantages of being bilingual, including maintaining a cultural and linguistic heritage and conferring an advantage in the ability to communicate with a broader population in future social, educational, and work environments. Additionally, an emerging field of research, albeit with mixed results to date, explores potential advantages of being bilingual that are linked more directly to cognitive development, starting in early childhood and extending to preserving cognitive function and delaying the symptoms of dementia in the elderly ( Bialystok, 2011 ; de Bruin et al., 2015 ).

Bilingual or multilingual children are faced with more communicative challenges than their monolingual peers. A child who frequently experiences failure to be understood or to understand may be driven to pay more attention to context, paralinguistic cues, and gestures in order to interpret an utterance, and thus become better at reading such cues. The result may be improved development of theory of mind and understanding of pragmatics ( Yow and Markman, 2011a , b ). In addition, the need to continually suppress one language for another affords ongoing practice in inhibitory or executive control, which could confer advantages on a range of inhibitory control tasks in children and helps preserve this fundamental ability in aging adults ( Bialystok, 2011 ; Bialystok and Craik, 2010 ; Bialystok et al., 2009 ).

One challenge in the education of dual language learners is that they sometimes are classified along with children with special needs. One reason for this is the lack of good assessment tools to help distinguish the nature of the difficulties experienced by dual language learners—whether due to a learning disability or to the fact that learning a second language is difficult, takes time, and develops differently in different children ( Hamayan et al., 2013 ).

Mathematics

Children's early knowledge of mathematics is surprisingly important, and it strongly predicts later success in mathematics ( Denton and West, 2002 ; Koponen et al., 2013 ; Passolunghi et al., 2007 ). Mathematics knowledge in preschool predicts mathematics achievement even into high school ( National Mathematics Advisory Panel, 2008 ; NRC, 2009 ; Stevenson and Newman, 1986 ). Mathematics ability and language ability also are interrelated as mutually reinforcing skills ( Duncan et al., 2007 ; Farran et al., 2005 ; Lerkkanen et al., 2005 ; O'Neill et al., 2004 ; Praet et al., 2013 ; Purpura et al., 2011 ). Indeed, mathematical thinking reaches beyond competence with numbers and shapes to form a foundation for general cognition and learning ( Clements and Sarama, 2009 ; Sarama et al., 2012 ), and problems with mathematics are the best predictor of failure to graduate high school. Mathematics therefore appears to be a core subject and a core component of thinking and learning ( Duncan and Magnuson, 2011 ; Duncan et al., 2007 ).

Given its general importance to academic success ( Sadler and Tai, 2007 ), children need a robust foundation in mathematics knowledge in their earliest years. Multiple analyses suggest that mathematics learning should begin early, especially for children at risk for later difficulties in school ( Byrnes and Wasik, 2009 ; Clements and Sarama, 2014 ). Well before first grade, children can learn the skills and concepts that support more complex mathematics understanding later. Particularly important areas of mathematics for young children to learn include number, which includes whole number, operations, and relations; geometry; spatial thinking; and measurement. Children also need to develop proficiency in processes for both general and specific mathematical reasoning ( NRC, 2009 ).

If given opportunities to learn, young children possess a remarkably broad, complex, and sophisticated—albeit informal—knowledge of mathematics ( Baroody, 2004 ; Clarke et al., 2006 ; Clements et al., 1999 ; Fuson, 2004 ; Geary, 1994 ; Thomson et al., 2005 ). In their free play, almost all preschoolers engage in substantial amounts of premathematical activity. They count objects; compare magnitudes; and explore patterns, shapes, and spatial relations. Importantly, this is true regardless of a child's income level or gender ( Seo and Ginsburg, 2004 ). Preschoolers can also, for example, learn to invent solutions to simple arithmetic problems ( Sarama and Clements, 2009 ).

High-quality mathematics education can help children realize their potential in mathematics achievement ( Doig et al., 2003 ; Thomson et al., 2005 ). However, without such education starting, and continuing throughout, the early years, many children will be on a trajectory in which they will have great difficulty catching up to their peers ( Rouse et al., 2005 ). As discussed further in Chapter 6 , early childhood classrooms typically are ill suited to helping children learn mathematics and underestimate their ability to do so. In some cases, children can even experience a regression on some mathematics skills during prekindergarten and kindergarten ( Farran et al., 2007 ; Wright, 1994 ). Mathematics needs to be conceptualized as more than skills, and its content as more than counting and simple shapes. Without building a robust understanding of mathematics in the early years, children too often come to believe that math is a guessing game and a system of rules without reason ( Munn, 2006 ).

Both education and experience can make a difference, as evidenced by data from the latest international Trends in International Mathematics and Science Study, which added data collection on early mathematics education ( Mullis et al., 2012 ). Students with higher mathematics achievement at fourth and sixth grades had parents who reported that they often engaged their children in early numeracy activities and that their children had attended preprimary education and started school able to do early numeracy tasks (e.g., simple addition and subtraction). Those children who had attended preschool or kindergarten had higher achievement, while the 13 percent who had attended no preprimary school had much lower average mathematics achievement ( Mullis et al., 2012 ).

Developmental Progression of Learning Mathematics

Children move through a developmental progression in specific mathematical domains, which informs learning trajectories as important tools for supporting learning and teaching. Recent work based on empirical research and emphasizing a cognitive science perspective conceptualizes learning trajectories for mathematics as “descriptions of children's thinking and learning in a specific mathematical domain, and a related, conjectured route through a set of instructional tasks designed to engender those mental processes or actions hypothesized to move children through a developmental progression of levels of thinking, created with the intent of supporting children's achievement of specific goals in that mathematical domain” ( Clements and Sarama, 2004 , p. 83).

Box 4-5 illustrates the concept of a developmental progression through the example of subitizing , an oft-neglected mathematical goal for young children. Research shows that subitizing, the rapid and accurate recognition of the number in a small group, is one of the main abilities very young children should develop ( Palmer and Baroody, 2011 ; Reigosa-Crespo et al., 2013 ). Through subitizing, children can discover critical properties of number, such as conservation and compensation ( Clements and Sarama, 2014 ; Maclellan, 2012 ) and develop such capabilities as unitizing and arithmetic. Subitizing is not the only way children think and learn about number. Counting is the other method of quantification. It is the first and most basic mathematical algorithm and one of the more critical early mathematics competencies ( Aunola et al., 2004 ; National Mathematics Advisory Panel, 2008 ). Chapter 6 includes examples from a complete learning trajectory—goal, developmental progression, and instructional activities—for counting ( Clements and Sarama, 2014 ).

Subitizing: A Developmental Progression. A quantitative, or numerical, “sense” is innate or develops early. For example, very young children possess approximate number systems (ANSs) that allow them to discriminate large and small sets, (more...)

Children with Special Needs

Children with special needs in learning mathematics fall into two categories. Those with mathematical difficulties struggle to learn mathematics for any reason; this category may apply to as many as 35-40 percent of students ( Berch and Mazzocco, 2007 ). Those with specific mathematics learning disabilities are more severe cases; these students have a memory or cognitive deficit that interferes with their ability to learn math ( Geary, 2004 ). This category may apply to about 6-7 percent ( Berch and Mazzocco, 2007 ; Mazzocco and Myers, 2003 ). In one study, this classification persisted in third grade for 63 percent of those classified as having mathematics learning disabilities in kindergarten ( Mazzocco and Myers, 2003 ).

Mathematics learning disabilities, while assumed to have a genetic basis, currently are defined by students' behaviors—yet with ongoing debate among experts about what those behaviors are. One consistent finding is that students with mathematics learning disabilities have difficulty retrieving basic arithmetic facts quickly. This has been hypothesized to be the result of an inability to store or retrieve facts and impairments in visual-spatial representation. As early as kindergarten, limited working memory and speed of cognitive processing may be problems for these children ( Geary et al., 2007 ). Many young children with learning disabilities in reading show a similar rapid-naming deficit for letters and words ( Siegel and Mazabel, 2013 ; Steacy et al., 2014 ). Another possibility is that a lack of higher-order, or executive, control of verbal material causes difficulty learning basic arithmetic facts or combinations. For example, students with mathematics learning disabilities may have difficulty inhibiting irrelevant associations. An illustration of this would be hearing “5 + 4” and saying “6” because it follows 5.

One explanation for the difficulty students with mathematics learning disabilities have learning basic arithmetic combinations might be delays in understanding counting. These students may not fully understand counting nor recognize errors in counting as late as second grade. They persist in using immature counting strategies, such as counting “one-by-one” on their fingers, throughout elementary school ( Geary et al., 1992 ; Ostad, 1998 ). Other experts, however, claim that a lack of specific competencies, such as subitizing, is more important ( Berch and Mazzocco, 2007 ).

Some evidence suggests that it is possible to predict which kindergartners are at risk for mathematics learning disabilities based on skill including reading numerals, number constancy, magnitude judgments of one-digit numbers, or mental addition of one-digit numbers ( Mazzocco and Thompson, 2005 ). However, until more is known, students should be classified as having mathematics learning disabilities only with great caution and after good mathematics instruction has been provided. Such labeling in the earliest years could do more harm than good ( Clements and Sarama, 2012 ).

Interrelationships Between Mathematics and Language

It can appear that language is less of a concern in mathematics compared to other subjects because it is assumed to be based on numbers or symbols, but this is not the case ( Clements et al., 2013a ). In fact, children learn math mainly from oral language, rather than from mathematical symbolism or textbooks ( Janzen, 2008 ). In addition, “talking math” is more than just using mathematics terms ( Clements and Sarama, 2014 ). Therefore, both oral language and literacy in general, as well as the “language of mathematics,” are important for learning ( Vukovic and Lesaux, 2013 ). Vocabulary and knowledge of print are both predictors of later numeracy ( Purpura et al., 2011 ). Similarly, growth in mathematics from kindergarten to third grade is related to both early numerical skills and phonological processing ( Vukovic, 2012 ). In one study of linguistically and ethnically diverse children aged 6-9 years, language ability predicted gains in geometry, probability, and data analysis but not in arithmetic or algebra (controlling for reading ability, visual–spatial working memory, and gender) ( Vukovic and Lesaux, 2013 ). Thus, language may affect how children make meaning of mathematics but not its complex arithmetic procedures.

Moreover, there is an important bidirectional relationship between learning in mathematics and language ( Sarama et al., 2012 ). Each has related developmental milestones. Children learn number words at the same time as other linguistic labels. Most children recognize by the age of 2 which words are for numbers and use them only in appropriate contexts ( Fuson, 1988 ). Each also has related developmental patterns, with learning progressing along similar paths. In both, children recognize the whole before its parts. In learning language, this is word before syllable, syllable before rime-onset, and rime-onset before phoneme (see also Anthony et al., 2003 ; Ziegler and Goswami, 2005 ). Similarly in mathematics, numbers are first conceptualized as unbreakable categories and then later as composites (e.g., 5 is composed of 3 and 2) ( Butterworth, 2005 ; Sarama and Clements, 2009 ). By 6 years old in most cultures, children have been exposed to symbol representations that are both alphabetic and numerical, and they begin to be able to segment words into phonemes and numbers into singletons (e.g., understanding that 3 is 1 and 1 and 1) ( Butterworth, 2005 ; Sarama and Clements, 2009 ; Wagner et al., 1993 ). The ability to identify the component nature of words and numbers predicts the ability to read ( Adams, 1990 ; Stanovich and Siegel, 1994 ) and to compute ( Geary, 1990 , 1993 ). In addition to these similarities in typical developmental pathways, many children with learning disabilities experience deficits in competencies related to both language/literacy and numeracy ( Geary, 1993 ; Hecht et al., 2001 ; NRC, 1998 ).

Furthermore, there appear to be shared competencies between the two subject areas. For example, preschoolers' narrative abilities (i.e., their abilities to convey all the main events of a story and offer a perspective on its events) have been shown to predict mathematics achievement 2 years later ( O'Neill et al., 2004 ). Beginning mathematics scores have been shown to be highly predictive of subsequent achievement in both reading and mathematics although beginning reading skills (such as letter recognition, word identification, and word sounds) were shown to be highly predictive of later reading (advanced competencies such as evaluation) but not mathematics learning ( Duncan et al., 2007 ).

A causal relationship between rich mathematics learning and developing language and literacy skills is supported by a randomized study of the effects of a math curriculum called Building Blocks on prekindergarten children's letter recognition and oral language skills. Building Blocks children performed the same as the children in the control group on letter recognition and on three oral language subscales but outperformed them on four subscales: ability to recall key words, use of complex utterances, willingness to reproduce narratives independently, and inference ( Sarama et al., 2012 ). These skills had no explicit relation to the math curriculum. Similarly, a study of 5- to 7-year-olds showed that an early mathematics and logical-mathematical intervention increased later scores in English by 14 percentile points ( Shayer and Adhami, 2010 ).

Time on task (or time on instruction) does affect learning, which naturally leads to consideration of potential conflicts or tradeoffs between time spent on different subjects (e.g., Bodovski and Farkas, 2007 ). Indeed, a frequent concern is that introducing a mathematics curriculum may decrease the time devoted to language and literacy, impeding children's development in those areas, which are heavily emphasized in early learning goals (see Clements and Sarama, 2009 ; Farran et al., 2007 ; Lee and Ginsburg, 2007 ; Sarama and Clements, 2009 ). However, this assumes that mathematics activities will not have a positive effect on language and literacy. Yet as described here, evidence from both educational and psychological research suggests the potential for high-quality instruction in each to have mutual benefits for learning in both subjects. Rich mathematical activities, such as discussing multiple solutions and solving narrative story problems, can help lay the groundwork for literacy through language development, while rich literacy activities can help lay the groundwork for mathematics development ( Sarama et al., 2012 ).

Children Who Are Dual Language Learners

For mathematics learning in children who are dual language learners, the language, not just the vocabulary, of mathematics need to be addressed ( Clements and Sarama, 2014 ). Challenges for dual language learners include both technical vocabulary, which can range in how similar or distinct terms are from everyday language, and the use of complex noun phrases. On the other hand, bilingual children often can understand a mathematical idea more readily because, after using different terms for it in different languages, they comprehend that the mathematical idea is abstract, and not tied to a specific term (see Secada, 1992 ).

There is evidence that the best approach is to teach these young children in their first language ( Celedón-Pattichis et al., 2010 ; Espada, 2012 ). At a minimum, their teachers need to connect everyday language with the language of math ( Janzen, 2008 ). It is also essential to build on the resources that bilingual children bring to learning mathematics—all cultures have “funds of knowledge” (culturally developed and historically accumulated bodies of knowledge and skills) that can be used to develop mathematical contexts and understandings ( Moll et al., 1992 ). Instructional practices for teaching mathematics with dual language learners are discussed further in Chapter 6 .

Conclusions About Learning Specific Subjects For subject-matter content knowledge and proficiency, children learn best when supported along a trajectory with three components: (1) their understanding of the subject-matter content itself, (2) their progress through predictable developmental levels and patterns of thinking related to their understanding of the content, and (3) instructional tasks and strategies that adults who work with children can employ to promote that learning at each level. For example: Almost all topics in mathematics follow predictable learning trajectories that include number counting and subitizing, number relationships and magnitude comparison, arithmetic operations, geometry and spatial sense, and measurement. Learning trajectories in literacy include specific developmental sequences in children's learning of phonological awareness and phonics (letter-sound correspondences), which together contribute to children's understanding of how spoken words are captured in reading and writing and thus to their advancement through broader levels of early literacy. Some principles of how children learn along a trajectory hold across subject-matter domains, but there are also substantive differences among subjects in the specific skills children need and in the learning trajectories. Both generalizable principles and subject-specific distinctions have implications for the knowledge and competencies needed to work with children. An important factor in children's learning of subject-matter content is how each of the components of learning trajectories both requires and develops aspects of learning that are not content specific, such as critical reasoning, executive function, self-regulation, learning skills, positive dispositions toward learning, and relationships.

• GENERAL LEARNING COMPETENCIES

Educators, developmental scientists, and economists have long known that academic achievement is a result of both the growth of specific knowledge and the development of general learning competencies that regulate how children enlist cognitive resources when they encounter learning challenges, motivate advances in learning, and strengthen children's self-confidence as learners.

These general learning competencies have been labeled and categorized in various ways. Considerable recent research on some of these learning competencies has been conducted using the concept of “executive function,” which generally refers to a set of supervisory functions that regulate and control cognitive activity that affects learning ( Vitiello et al., 2011 ) and allow children to persevere with tasks, including learning tasks, even when facing fatigue, distraction, or decreased motivation. In the field of human development “mastery motivation” in infancy typically is indexed by the baby's persistence, focus, and curiosity in exploration and problem solving ( Morgan et al., 1990 ; Wang and Barrett, 2013 ). In preschool-age children, these skills often are conceptualized as the quality of the child's “approaches to learning,” which include motivation, engagement, and interest in learning activities. Heckman (2007) has used the term “noncognitive skills” to refer to many of these learning competencies, including self-control, persistence, self-discipline, motivation, and self-esteem, as well as future orientedness (i.e., the capacity to substitute long-term goals for immediate satisfactions). This label is used in contrast to the “cognitive skills” that are more often measured to predict children's later success, although there is considerable research that the “noncognitive skills” also support learning and achievement (see, e.g., Cunha and Heckman, 2010 ; Heckman, 2007 ), and they are highly relevant to cognitive skills in such areas as language, mathematics, science, and other traditional academic fields.

Here the alternative conceptualizations for these important aspects of child development and early learning are grouped as “learning competencies” to reflect their importance for early learning. Individual differences in these competencies are important determinants of learning and academic motivation, and children's experiences at home and in the classroom contribute to some of these differences. This section examines these competencies as well as their interrelationships with the previously discussed subject-matter domains of language and literacy and mathematics.

General Cognitive Skills

Several cognitive control processes are important for planning and executing goal-directed activity, which is needed for successful learning (e.g., Blair, 2002 ; Lyon and Krasnegor, 1996 ). These processes include, for example, short-term and working memory, attention control and shifting, cognitive flexibility (changing thinking between different concepts and thinking about multiple concepts simultaneously), inhibitory control (suppressing unproductive responses or strategies), and cognitive self-regulation. These processes also are closely related to emotion regulation, which is discussed later in the section on socioemotional development, and which also contributes to children's classroom success.

As noted previously, many general cognitive processes often are referred to collectively as “executive function,” although not everyone defines this construct in the same way (e.g., Miyake et al., 2000 ; Raver, 2013 ), and different disciplines and researchers differ as to which cognitive skills it includes. Other theoretical frameworks exist as well. For example, cognitive control and complexity theory postulates that executive function is an outcome, not an explanatory construct, and is the result of children's creation and application of rules (driven perhaps by an increase in reflection afforded by experience-dependent maturation of the prefrontal cortex) ( Müller et al., 2008 ; Zelazo and Carlson, 2012 ; Zelazo and Lyons, 2012 ). As with the overall domains of development displayed earlier in Figure 4-1 , the committee did not attempt to reconcile those different perspectives.

This variation in perspectives makes it difficult to parse the literature produced by different fields of research and practice. In general, however, executive function appears to improve most rapidly in young children ( Best et al., 2011 ; Blair, 2002 ; Hughes and Ensor, 2011 ; Romine and Reynolds, 2005 ; Schoemaker et al., 2014 ; Zelazo and Carlson, 2012 ). Executive function processes appear to be partially dependent on the development of the prefrontal cortex (the site of higher-order cognitive processes), notably through the preschool and kindergarten age range ( Bassett et al., 2012 ; Blair, 2002 ).

Short-Term and Working Memory

Short-term memory is the ability for short-term recall, such as of a sentence or important details from conversation and reading. Working memory allows children to hold in their memory information from multiple sources, whether heard or read, so they can use and link that information. Updating working memory is the ability to keep and use relevant information while engaging in another cognitively demanding task ( Conway et al., 2003 ; DeYoung, 2011 ).

Attention Control and Shifting

Attention control is the ability to focus attention and disregard distracting stimuli (e.g., a continuous performance task that requires a child to identify when some familiar object appears onscreen and ignore other objects that appear, or a task that requires ignoring extraneous information in a mathematics word problem). Attention shifting is a related process of switching a “mental set” while simultaneously ignoring distractions (e.g., counting by different units—tens and ones). Attention shifting and cognitive flexibility are often grouped.

Cognitive Flexibility

Cognitive flexibility capacities develop gradually throughout early childhood and have significant influences on children's social and academic competence. Cognitive flexibility is important, for example, for reading ( Duke and Block, 2012 ). Children who are better able to consider, at the same time, both letter-sound and semantic (meaning) information about words have better reading comprehension ( Cartwright, 2002 ; Cartwright et al., 2010 ). Reading comprehension also appears to improve when children are taught about words with multiple meanings (e.g., spell or plane ), and sentences with multiple meanings (e.g., “The woman chased the man on a motorcycle.”) ( Yuill, 1996 ; Zipke et al., 2009 ). In addition, interventions in young children that focus on cognitive flexibility have shown significant benefits for reading comprehension ( Cartwright, 2008 ).

Inhibitory Control

Inhibitory control involves controlling a dominant response (e.g., the first answer that comes to mind) so as to think about better strategies or ideas. The skill of simple response inhibition (withholding an initial, sometimes impulsive, response) develops during infancy through toddlerhood. Infants also develop some control of cognitive conflict in tasks in which an item of interest to them is first hidden in one location and then another, and the child must resist the response of searching in the first location ( Diamond, 1991 ; Müller et al., 2008 ; Rothbart and Rueda, 2005 ) (see Marcovitch and Zelazo, 2009 , for a model of possible mechanisms). Later in their first year, children can resolve conflict between their line of sight and their line of reaching ( Diamond, 1991 ). By about 30 months, they can successfully complete a spatial conflict task ( Rothbart and Rueda, 2005 ). From 3 to 5 years of age, complex response inhibition and response shifting develop, with attention shifting developing at about age 4 ( Bassett et al., 2012 ). The most rapid increase in inhibitory control is between 5 and 8 years of age, although moderate improvements are seen up to young adulthood ( Best et al., 2011 ).

Inhibitory control supports children's learning across subject-matter areas. As one example of its importance for mathematics, when the initial reading of a problem is not the correct one, children need to inhibit their impulse to answer (incorrectly) and carefully examine the problem. Consider the following problem: “There were six birds in a tree. Three birds already flew away. How many birds were there from the start?” Children have to inhibit the immediate desire to subtract prompted by the words “flew away” and perform addition instead.

Cognitive Self-Regulation

Cognitive self-regulation is what helps children plan ahead, focus attention, and remember past experiences. The construct of self-regulation and related concepts have a long history in psychology (e.g., Glaser, 1991 ; Markman, 1977 , 1981 ; Piaget and Szeminska, 1952 ; Sternberg, 1985 ; Vygotsky, 1978 ; Zelazo et al., 2003 ) and education (e.g., McGillicuddy-De Lisi, 1982 ; Steffe and Tzur, 1994 ). Most recently, researchers and educators have used the broad term self-regulation to refer to the processes involved in intentionally controlling attention, thinking, impulses, emotions, and behavior. In this way, self-regulation can be thought of in relation to several aspects of development, including the cognitive processes discussed here and the social and emotional processes discussed later in this chapter. Developmental psychobiological research and neuroimaging indicate that these subclasses are both neurally and behaviorally distinct while also being related and correlated ( Bassett et al., 2012 ; Hofmann et al., 2012 ; Hongwanishkul et al., 2005 ; Neuenschwander et al., 2012 ; Willoughby et al., 2011 ). Together, these types of self-regulation allow children to persevere with tasks even when facing difficulties in problem solving or learning, fatigue, distraction, or decreased motivation ( Blair and Razza, 2007 ; Neuenschwander et al., 2012 ). It is thus unsurprising that kindergarten teachers believe self-regulation is as important as academics ( Bassok and Rorem, 2014 ).

Both cognitive self-regulation and emotional self-regulation (discussed later in this chapter) contribute to socioemotional development and also play a role in learning. Although the relationship between various features of cognitive self-regulation and academic achievement has been well documented for older students (e.g., Bielaczyc et al., 1995 ; Zimmerman, 2002 ), less was known until recently about how self-regulation developed in the early years contributes to the later development of cognitive and emotional self-regulation and academic achievement ( NRC and IOM, 2000 ).

Children's self-regulation and their ability to successfully function in school settings are related in two ways. First, emotional self-regulation enables children to benefit from learning in various social contexts, including their capacities to manage emotions in interactions with educators as well as peers (e.g., one-on-one, in cooperative pairs, in large and small groups). It also assists them in conforming to classroom rules and routines. Second, cognitive self-regulation enables children to develop and make use of cognitive processes that are necessary for academic learning ( Anghel, 2010 ).

Although most studies have focused on specific effects of either cognitive or emotional self-regulation, evidence suggests that the two are interconnected. This link is probably due to the commonality of the neurological mechanisms governing both emotional and cognitive self-regulation. For example, children lacking emotion regulation are likely also to have problems with regulating cognitive processes, such as attention ( Derryberry and Reed, 1996 ; LeDoux, 1996 ). Moreover, earlier patterns in the development of emotion control have been shown to be predictive of children's later ability to exercise control over their cognitive functioning ( Blair, 2002 ).

Several studies have shown positive correlations between self-regulation and achievement in young children (e.g., Bierman et al., 2008b ; Blair and Razza, 2007 ; Blair et al., 2010 ; Bull et al., 1999 ; Cameron et al., 2012 ; Neuenschwander et al., 2012 ; Roebers et al., 2012 ; Welsh et al., 2010 ), although there are exceptions ( Edens and Potter, 2013 ). Preschoolers' cognitive self-regulation, including inhibitory control and attention shifting, were found to be related to measures of literacy and mathematics ability in kindergarten ( Blair and Razza, 2007 ). In another study, children with higher self-regulation, including attention, working memory, and inhibitory control, achieved at higher levels in literacy, language, and mathematics ( McClelland et al., 2007 ). Interventions in the area of self-regulation have shown positive effects for reading achievement ( Best et al., 2011 ; Bierman et al., 2008a ; Blair and Diamond, 2008 ; Blair and Razza, 2007 ; Diamond and Lee, 2011 ). Among struggling first graders in an effective reading intervention, those who were retained in grade showed significantly weaker self-regulation skills ( Dombek and Connor, 2012 ). Cognitive self-regulation appears to be strongly associated with academic learning ( Willoughby et al., 2011 ), but emotional self-regulation also contributes through children's adjustment to school and attitudes toward learning. In addition, both cognitive and emotional self-regulation contribute to variance in attention, competence motivation, and persistence ( Bassett et al., 2012 ; Willoughby et al., 2011 ).

In addition, differences in self-regulation competencies raise important issues related to disparities in educational achievement. Children in poverty can have lower self-regulation competencies (e.g., Blair and Razza, 2007 ; Blair et al., 2010 ; Bull and Scerif, 2001 ; Hackman and Farah, 2009 ; Jenks et al., 2012 ; Kishiyama et al., 2009 ; Masten et al., 2012 ; Mazzocco and Hanich, 2010 ; McLean and Hitch, 1999 ; Raver, 2013 ). One reason is the effect of chronic stress on behavioral and biological capacities for self-control (see discussion of chronic stress and adversity later in this chapter). This risk is exacerbated for children who are also dual language learners ( Wanless et al., 2011 ). Students with special needs are another population who may require focused interventions to develop self-regulation competencies ( Harris et al., 2005 ; Jenks et al., 2012 ; Lyon and Krasnegor, 1996 ; Mazzocco and Hanich, 2010 ; McLean and Hitch, 1999 ; Raches and Mazzocco, 2012 ; Toll et al., 2010 ; Zelazo et al., 2002 ). Students who are gifted and talented may also have exceptional needs in this domain (e.g., Mooji, 2010 ).

Adults who work with children have the opportunity to provide environments, experiences, and curricula that can help develop the competencies needed, including for children whose skills were not optimally developed in the earliest years. Importantly, the goal of such interventions is not to “train” children to suppress behaviors and follow rules. Rather, effective educators and programs provide learning activities and environments that increase children's capacity and disposition to set a goal (e.g., join a pretend play activity, complete a puzzle); develop a plan or strategy; and muster their social, emotional, and cognitive faculties to execute that plan. The science of how children develop and learn indicates that integrating academic learning and self-regulation is a sound approach.

Executive Functions and Learning in Specific Subjects

As already noted and shown in several examples, executive function processes are closely related to achievement in both language and literacy and mathematics ( Best et al., 2011 ; Blair and Razza, 2007 ; Blair et al., 2010 ; Neuenschwander et al., 2012 ), and this has also been shown in science ( Nayfeld et al., 2013 ). In some research, executive function has been correlated similarly with both reading and mathematics achievement across a wide age span (5 to 17 years), suggesting its significant role in academic learning ( Best et al., 2011 ; Blair and Razza, 2007 ; Neuenschwander et al., 2012 ). In contrast, some studies have found that executive function is more strongly associated with mathematics than with literacy or language ( Barata, 2010 ; Blair et al., 2010 ; Ponitz et al., 2009 ; von Suchodoletz and Gunzenhauser, 2013 ). A strong relationship between executive function and mathematics may reflect that mathematics relies heavily on working memory and attention control, requiring the ability to inhibit an automatic response to a single aspect of a problem, to hold relevant information in mind, and to operate on it while shifting attention appropriately among different elements of a problem ( Welsh et al., 2010 ). This relationship is especially important given that mathematics curricula increasingly require higher-order skills, which executive function competencies provides ( Baker et al., 2010 ).

Some research indicates that most executive function competencies correlate significantly with mathematics achievement ( Bull and Scerif, 2001 ), while other studies suggest a greater role for particular executive function competencies in the learning of mathematics for young children—especially inhibitory control ( Blair and Razza, 2007 ) or working memory ( Bull et al., 2008 ; Geary, 2011 ; see also, Geary et al., 2012 ; cf. Neuenschwander et al., 2012 ; Szűcs et al., 2014 ; Van der Ven et al., 2012 ). These latter two competencies have been shown to predict success in mathematics in primary school students ( Toll et al., 2010 ). Working memory tasks have also been shown to predict mathematics learning disabilities, even more so than early mathematical abilities ( Toll et al., 2010 ). Several studies have identified lack of inhibition and working memory as specific deficits for children of lower mathematical ability, resulting in difficulty with switching to and evaluating new strategies for dealing with a particular task ( Bull and Scerif [2001] and Lan and colleagues [2011] found similar results). Persistence, another learning skill that is interrelated with cognitive processes, also has been linked to mathematics achievement for both 3- and 4-year-olds ( Maier and Greenfield, 2008 ).

Executive function competencies may be differentially associated with distinct areas of mathematics. For example, executive function was found to be correlated more with solving word problems than with calculation ( Best et al., 2011 ), and appears to play a role in acquiring new mathematics procedures and developing automatic access to arithmetic facts ( LeFevre et al., 2013 ). Different aspects of working memory also may be related to different mathematical areas ( Simmons et al., 2012 ). Parallel observations have been made for executive function and reading, with executive function playing a larger role in reading comprehension than in decoding.

In addition to the role of executive function in learning mathematics, mathematics activities also contribute to developing executive function. Some mathematics activities may require children to suppress prepotent responses, manipulate abstract information, and remain cognitively flexible. Importantly, neuroimaging studies suggest that executive function may be developed through learning mathematics in challenging activities but not in exercising mathematics once learned ( Ansari et al., 2005 ; Butterworth et al., 2011 ).

Cognitive Skills and Executive Function in Children with Special Needs

Some students with special needs may have a specific lack of certain executive function competencies ( Harris et al., 2005 ; Jenks et al., 2012 ; Lyon and Krasnegor, 1996 ; McLean and Hitch, 1999 ; Raches and Mazzocco, 2012 ; Schoemaker et al., 2014 ; Toll et al., 2010 ; Zelazo et al., 2002 ). Most of the research on executive function deficits in relation to disabilities that affect young children has focused on specific disorders, particularly attention deficit hyperactivity disorder (ADHD). An early theory posited that ADHD is a lack of the behavioral inhibition required for proficiency with executive functions such as self-regulation of affect, motivation, and arousal; working memory; and synthesis analysis of internally represented information ( Barkley, 1997 ). Research has found that children diagnosed with ADHD are more likely than children without ADHD to have two or more deficits in executive function ( Biederman et al., 2004 ; cf. Shuai et al., 2011 ). A meta-analysis of studies of one measure of executive function, the Wisconsin Card Sorting Test, suggests that the performance of individuals with ADHD is fairly consistently poorer than that of individuals without clinical diagnoses ( Romine et al., 2004 ). In another study, children with ADHD were found not to have learning problems but rather problems in a measure of inhibitory control, which affected arithmetic calculation (as well as written language) ( Semrud-Clikeman, 2012 ). Other evidence suggests that children diagnosed with ADHD may have deficits not in executive processes themselves but in motivation or response to contingencies, that is, the regulation of effort allocation ( Huang-Pollock et al., 2012 ).

Having ADHD with deficits in executive function, compared to ADHD alone, is associated with an increased risk for grade retention and a decrease in academic achievement ( Biederman et al., 2004 ). The relationship between ADHD and executive functions may also depend on subtype. One study found that children with an inattention ADHD subtype showed deficits in several executive function competencies ( Tymms and Merrell, 2011 ), whereas children with the hyperactive-impulsive ADHD subtype may have fewer executive function deficits ( Shuai et al., 2011 ) and may even have strengths that could be developed in appropriate educational environments.

Deficits in executive function have been studied in other developmental disorders as well, albeit often in less detail. They include autism ( Bühler et al., 2011 ; Hill, 2004 ; Zelazo et al., 2002 ); attention and disruptive behavior problems ( Fahie and Symons, 2003 ; Hughes and Ensor, 2011 ); intellectual disabilities ( Nader-Grosbois and Lefèvre, 2011 ; Neece et al., 2011 ; Vieillevoye and Nader-Grosbois, 2008 ); cerebral palsy ( Jenks et al., 2012 ); Turner syndrome ( Mazzocco and Hanich, 2010 ); developmental dyslexia ( Brosnan et al., 2002 ; cf. Romine and Reynolds, 2005 ); and mathematics learning disabilities ( Toll et al., 2010 ).

Other Learning Skills and Dispositions

Other learning skills that are important to early academic achievement include persistence, curiosity, self-confidence, intrinsic motivation, time perspective (e.g., the willingness to prioritize long-term goals over immediate gratifications), and self-control. The growth of emotional and cognitive self-regulation is also fundamentally related to many of these developing learning skills. In addition, social experiences, discussed later in this chapter, are important for the growth of these learning skills. Note also that although these skills are referred to sometimes as dispositions, they are fostered through early experience and can be supported through intentional caregiving and instructional practices; they are not simply intrinsic traits in the child.

A capacity for focused engagement in learning is apparent from very early in life, although it is also true that these learning competencies develop significantly throughout early childhood as processes of neurobiological development interact with children's social experiences to enable greater persistence, focused attention, delayed gratification, and other components of effective learning and problem solving. As a consequence, very young children are likely to approach new learning situations with enthusiasm and self-confidence but at young ages may not necessarily bring persistence or creativity in confronting and solving challenging problems. Older preschoolers, by contrast, are more self-regulated learners. They approach new learning opportunities with initiative and involvement, and they are more persistent and more likely to solve problems creatively, by proposing their own ideas ( NRC, 2001 ).

Considerable research confirms the importance of these skills to early learning. Individual differences in infants' “mastery motivation” skills—persistence, focus, and curiosity in exploration and problem solving—predict later cognitive abilities and achievement motivation ( Busch-Rossnagel, 2005 ; Morgan et al., 1990 ; Wang and Barrett, 2013 ). In preschool-age children, learning skills that include motivation, engagement, and interest in learning activities have been found in longitudinal studies to predict children's cognitive skills at school entry ( Duncan et al., 2005 , 2007 ). Similarly, these characteristics continue to be associated with reading and mathematics achievement in the early elementary grades ( Alexander et al., 1993 ). Differences in these learning skills are especially associated with academic achievement for children in circumstances of economic disadvantage who face various kinds of self-regulatory challenges ( Blair and Raver, 2012 ; Howse et al., 2003a ).

Much of school success requires that children prioritize longer-term rewards requiring current effort over immediate satisfactions. The classic demonstration of this skill comes from a series of studies led by Walter Mischel beginning in the 1960s. Young children were offered the option of choosing an immediate, smaller reward or a larger reward if they waited to receive it later. For several years developmental outcomes for these children were tracked, which revealed that children who were better able to delay gratification at age 4 scored higher on measures of language skills, academic achievement, planful behaviors, self-reliance, capacity to cope with stress and frustration, and social competence measured in adolescence and adulthood ( Mischel et al., 1988 ). Other studies have reported consistent findings. Early development in the ability to prioritize future, long-term goals over short-term lesser gains improves children's chances of academic achievement and securing and maintaining employment ( Rachlin, 2000 ). Conversely, the inability to delay gratification is associated with young children's aggressive behavior, conduct problems, poorer peer relationships, and academic difficulty during preschool and the transition to elementary school ( Olson and Hoza, 1993 ) as well as later outcomes, including academic failure, delinquency, and substance abuse in adolescence ( Lynam et al., 1993 ; Wulfert et al., 2002 ).

The ways that children view themselves as learners are also important. Young children's self-perceived capability to master learning challenges develops early and exerts a continuing influence on their academic success. Early self-evaluations of competence are based on the positive and negative evaluations of children's behavior and competence by parents ( Stipek et al., 1992 ). Parent and educator expectations for children's success remain important. High parent expectations for children's school achievement are associated with children's later academic performance, and this is also true of educator expectations. In one longitudinal study, teacher expectations for children's math achievement in grades 1 and 3 directly predicted children's scores on standardized achievement tests 2 years later, and expectations for reading achievement had indirect associations with later reading scores. There was also evidence in this study that expectations were especially influential for academically at-risk students ( Hinnant et al., 2009 ).

Messages from parents and educators are also important in shaping how children attribute their own success and failure which, in turn, predicts their future effort and expectations of success. Children develop implicit theories in the early years about who they are as a person and what it means to be intelligent. Some children come to view intelligence as a fixed trait (i.e., one is either smart or not), whereas others see it as a more malleable trait that can be changed through effort and persistence. Educators and parents who approach learning goals by promoting and rewarding effort, persistence, and willingness to take on challenging problems increase children's motivation and their endorsement of effort as a path to success. In contrast, children receiving messages that intelligence is stable and cannot be improved through hard work are discouraged from pursuing difficult tasks, particularly if they view their abilities as low ( Heyman and Dweck, 1992 ). These patterns of “helpless” versus “mastery-oriented” motivation are learned in the preschool years and remain stable over time ( Smiley and Dweck, 1994 ).

These perceptions and patterns of motivation can be especially significant as children learn academic subjects, such as mathematics ( Clements and Sarama, 2012 ). People in the United States have many negative beliefs and attitudes about mathematics ( Ashcraft, 2006 ). One deeply embedded cultural belief is that achievement in mathematics depends mainly on native aptitude or ability rather than effort. Research shows that the belief in the primacy of native ability hurts students and, further, it is simply untrue.

Throughout their school careers, students who believe—or are helped to understand—that they can learn if they try working longer on tasks have better achievement than those who believe that either one “has it” (or “gets it”) or does not ( McLeod and Adams, 1989 ; Weiner, 1986 ). Researchers have estimated that students should be successful about 70 percent of the time to maximize motivation ( Middleton and Spanias, 1999 ). If students are directly assured that working hard to figure out problems, including making errors and being frustrated, are part of the learning process it can diminish feelings of embarrassment and other negative emotions at being incorrect. In contrast, students' learning can be impeded if educators define success only as rapid, correct responses and accuracy only as following the educator's example ( Middleton and Spanias, 1999 ). In addition, students will build positive feelings about mathematics if they experience it as a sense-making activity. Most young students are motivated to explore numbers and shapes and have positive feelings about mathematics ( Middleton and Spanias, 1999 ). However, after only a couple of years in typical schools, they begin to believe that only some people have the ability to do math.

A related pattern relating perceptions and emotions to learning is seen with students who experience mathematics anxiety. Primary grade students who have strong math anxiety, even alongside strong working memory, have been found to have lower mathematics achievement because working memory capacity is co-opted by math anxiety ( Beilock, 2001 ; Ramirez et al., 2013 ). Research has shown that primary grade students who “feel panicky” about math have increased activity in brain regions that are associated with fear, which decreases activity in brain regions associated with problem solving ( Young et al., 2012 ). Early identification and treatment of math anxiety may prevent children with high potential from avoiding mathematics and mathematics courses ( Ramirez et al., 2013 ).

• SOCIOEMOTIONAL DEVELOPMENT

The development of social and emotional competence is an important part of child development and early learning. Socioemotional competence has been described as a multidimensional construct that contributes to the ability to understand and manage emotions and behavior; to make decisions and achieve goals; and to establish and maintain positive relationships, including feeling and showing empathy for others. Although their importance is widely recognized, universal agreement is lacking on how to categorize and define these areas of development. The Collaborative for Academic, Social, and Emotional Learning offers a summary construct with five interrelated groups of competencies that together encompass the areas typically considered to be part of socioemotional competence (see Figure 4-2 ).

Elements of socioemotional competence. SOURCE: Collaborative for Academic, Social, and Emotional Learning (http://www.casel.org/social-and-emotional-learning/core-competencies, accessed March 24, 2015).

Socioemotional competence increasingly is viewed as important for a child's early school adjustment and for academic success at both the preschool and K-12 levels ( Bierman et al., 2008a , b ; Denham and Brown, 2010 ; Heckman et al., 2013 ; La Paro and Pianta, 2000 ; Leerkes et al., 2008 ). A growing body of research addresses the relationship between dimensions of socioemotional competence and cognitive and other skills related to early learning and later academic achievement ( Bierman et al., 2008a , b ; Graziano et al., 2007 ; Howse et al., 2003b ; Miller et al., 2006 ). Socioemotional development early in life also increasingly is understood to be critically important for later mental well-being, and for contributing to subsequent mental health problems when there are enduring disturbances in socioemotional functions ( IOM and NRC, 2009 ; Leckman and March, 2011 ).

There are several reasons why socioemotional development is important to early learning and academic success. As discussed in detail later in this section, early learning is a social activity in which these skills are important to the interactions through which learning occurs and is collaboratively shared. Socioemotional competence gives children the capacity to engage in academic tasks by increasing their ability to interact constructively with teachers, work collaboratively with and learn from peers, and dedicate sustained attention to learning ( Denham and Brown, 2010 ). Further, behavioral and emotional problems not only impede early learning but also pose other risks to long-term success. Substantial research has examined the relationship between delays and deficits in children's social skills and challenging behavior, such as serious problems getting along with peers or cooperating with educators ( Zins et al., 2007 ). When challenging behavior is not resolved during the early years, children with persistent early socioemotional difficulties experience problems in socialization, school adjustment, school success, and educational and vocational adaptation in adolescence and adulthood (e.g., Dunlap et al., 2006 ; Lane et al., 2008 ; Nelson et al., 2004 ). Thus attention to socioemotional competence also is important from the perspective of addressing early emerging behavior problems before they become more serious.

A variety of evidence-based approaches can be implemented to strengthen socioemotional competence for young children ( Domitrovich et al., 2012 ; IOM and NRC, 2009 ). These approaches typically entail strategies designed to improve children's emotion identification and understanding combined with the development of social problem-solving skills; practice in simple emotion regulation strategies; and coaching in prosocial behavior through strategies that can involve role playing, modeling, and reinforcement of socially competent behavior. Importantly, as discussed further in Chapter 6 , these strategies can be incorporated into daily classroom practice to provide children with everyday socioemotional learning.

Relational Security and Emotional Well-Being

As noted earlier in the discussion of self-regulation, socioemotional competencies contribute to the development of relationships with parents, educators, and peers. The development of positive relationships enables young children to participate constructively in learning experiences that are inherently social. The emotional support and security provided by positive relationships contributes in multifaceted ways to young children's learning success. Research on the security of attachment between young children and their parents illustrates this point, and provides a basis for considering the nature of children's relationships with educators and peers.

A secure parent–child attachment is widely recognized as foundational for healthy development, and the evolving understanding of the importance of attachment encompasses research in developmental psychology and developmental neuroscience (as discussed in Chapter 3 ) ( Schore and Schore, 2008 ; Thompson, 2013 ). Research has shown that securely attached children receive more sensitively responsive parental care, and in turn develop greater social skills with adults and peers and greater social and emotional understanding of others, show more advanced moral development, and have a more positive self-concept (see Thompson, 2013 , for a review). Securely attached children also have been found to be more advanced in cognitive and language development and to show greater achievement in school ( de Ruiter and van IJzendoorn, 1993 ; van Ijzendoorn et al., 1995 ; West et al., 2013 ). This association has been found for infants, preschool-age children, and older children, suggesting that it is fairly robust.

Most researchers believe that the association between attachment security and cognitive competence derives not from a direct link between the two, but from a number of processes mediating a secure attachment and the development of cognitive and language skills ( O'Connor and McCartney, 2007 ). The mediators that have been studied include the following:

• Early confidence and competence at exploration—One of the functions of a secure attachment is to enable infants and young children to better explore the environment, confident in the caregiver's support and responsiveness if things go awry. An extensive research literature, focused primarily on young children, confirms this expectation ( van Ijzendoorn et al., 1995 ). Early in life, exploratory interest is likely to lead to new discoveries and learning.
• Maternal instruction and guidance—Consistent with the sensitivity that initially contributes to a secure attachment, considerable research has shown that the mothers of securely attached children continue to respond supportively in ways that promote the child's social and cognitive achievements ( Thompson, in press) . In particular, these mothers talk more elaboratively with their children in ways that foster the children's deeper understanding and in so doing help support the children's cognitive growth ( Fivush et al., 2006 ). Furthermore, increased mother–child conversation is likely to foster the child's linguistic skills.
• Children's social competence with adults and peers—Securely attached children develop enhanced social skills and social understanding that enhance their competence in interactions with peers and adults in learning environments. In this light, their greater cognitive and language competencies may derive, at least in part, from more successful interactions with social partners in learning contexts. (See the detailed discussion of social interaction as a forum for cognitive growth later in this section.)
• Self-regulatory competence—Several studies suggest that securely attached children are more skilled in the preschool and early grade school years at self-regulation, especially as it is manifested in greater social competence and emotion regulation. Self-regulatory competence also may extend to children's greater attentional focus, cognitive self-control, and persistence in learning situations. In one recent report, the association of attachment security with measures of school engagement in the early primary grades was mediated by differences in children's social self-control; attentional impulsivity also varied with the security of attachment ( Drake et al., 2014 ; Thompson, 2013 ).
• Stress management—One of the functions of a secure attachment is that it supports the social buffering of stress by providing children with an adult who regularly assists them in challenging circumstances. The social buffering of stress may be an especially important aspect of how a secure attachment contributes to cognitive competence for children in disadvantaged circumstances when stress is likely to be chronic and potentially overwhelming (see Gunnar and Donzella, 2002 , for a review; Nachmias et al., 1996 ) (see also the discussion of chronic stress and adversity later in this chapter).

In addition to the substantial research on parent–child attachment and the development of cognitive competence, a smaller but significant research literature focuses on the development of attachments between children and educators and how those attachments contribute to children's success in structured learning environments (e.g., Ahnert et al., 2006 ; Birch and Ladd, 1998 ; Howes and Hamilton, 1992 ; Howes et al., 1998 ; Ladd et al., 1999 ; Mitchell-Copeland et al., 1997 ; Pianta and Stuhlman, 2004a , b ). In some respects, the processes connecting children's learning achievement with the supportive, secure relationships they develop with educators are similar to those observed with parent–child attachments. As with their parents and other caregivers, children develop attachments to their educators, and the quality of those relationships has a significant and potentially enduring influence on their classroom success ( Hamre and Pianta, 2001 ). Secure, warm relationships with educators facilitate young children's self-confidence when learning and assist in their self-regulatory competence, and there is evidence that children with such relationships in the classroom learn more than those who have more difficult relationships with educators ( NICHD Early Child Care Research Network, 2003 ; Pianta and Stuhlman, 2004b ).

In one study, preschoolers identified as academically at risk based on demographic characteristics and reports of problems by their kindergarten teachers were followed to the end of first grade ( Hamre and Pianta, 2005 ). The children with first-grade teachers who provided high amounts of instructional and emotional support had achievement scores comparable to those of their low-risk peers. Support was measured by teacher behaviors such as verbal comments promoting effort, persistence, and mastery; conversations using open-ended questions; encouragement of child responsibility; sensitivity; and a positive classroom climate. O'Connor and McCartney (2007) likewise found that positive educator–child relationships from preschool through third grade were associated with higher third-grade achievement, and that much of this achievement derived from how positive relationships promoted children's classroom engagement.

Positive educator–child relationships are especially important during the transition to school, when children's initial expectations about school and adjustment to its social demands take shape ( Ladd et al., 1999 ; Silver et al., 2005 ). Children who develop more positive relationships with their teachers in kindergarten are more positive about attending school, more excited about learning, and more self-confident. In the classroom they achieve more compared with children who experience more conflicted or troubled relationships with their teachers ( Birch and Ladd, 1997 ; NICHD Early Child Care Research Network, 2003 ; Pianta and Stuhlman, 2004b ). A positive relationship with educators may be especially important for children who are at risk of academic difficulty because such a relationship can provide support for self-confidence and classroom involvement ( Pianta et al., 1995 ).

A similar association is seen for peer relationships. Children who experience greater friendship and peer acceptance tend to feel more positive about coming to school, participate more in activities in the classroom, and achieve more in kindergarten ( Ladd et al., 1996 , 1997 ). Peer rejection is associated with less classroom participation, poorer academic performance, and a desire to avoid school ( Buhs and Ladd, 2001 ).

Taken together, research documenting the association between the security of attachment and the development of cognitive and language competence, as well as the stronger academic performance of securely attached children, highlights the multiple ways in which supportive relationships contribute to early learning. In particular, such relationships with parents, educators, and even peers provide immediate support that helps children focus their energies on learning opportunities, and they also foster the development of social and cognitive skills that children enlist in learning.

Emotion Regulation and Self-Management

Another element of socioemotional competence, touched on earlier in the section on general learning competencies, is self-regulation of emotion, or emotion regulation, which can affect learning behaviors and relationships with adults and peers. As noted in that earlier discussion, emotion regulation is closely intertwined with cognitive self-regulation and executive function. Emotion regulation processes include emotional and motivational responses to situations involving risk and reward (e.g., Kerr and Zelazo, 2004 ). They are frequently inhibitory; that is, they include the ability to suppress one response (e.g., grabbing a toy from another) so as to respond in a better way (asking for or sharing the toy). The development of emotion regulation and other forms of self-management in the early years is based on slowly maturing regions of the prefrontal cortex that continue to develop throughout adolescence and even early adulthood. Thus, early learners are maturationally challenged to manage their attention, emotions, and behavioral impulses effectively in a care setting or classroom.

Because they have difficulty cooperating or resolving conflicts successfully, children who lack effective self-regulation do not participate in a productive way in classroom activities—including learning activities ( Broidy et al., 2003 ; Ladd et al., 1999 ; Saarni et al., 1998 ). Children with poor emotion regulation skills may act disruptively and aggressively; they then receive less support from their peers, which in turn may undermine their learning ( Valiente et al., 2011 ). Poor emotion regulation also diminishes positive educator–child interactions, which, as discussed in the previous section, has been shown to predict poor academic performance and behavior problems ( Hamre and Pianta, 2001 ; Neuenschwander et al., 2012 ; Raver and Knitzer, 2002 ).

Coupled with joint attention and delay of gratification, self-regulation skills are linked to social competence and ease the transition to kindergarten ( Huffman et al., 2000 ; McIntyre et al., 2006 ). Children with difficulty regulating emotion in preschool and kindergarten often display inappropriate behavior, fail to pay attention (affecting whether they recall and process information), and have difficulty following instructions, all of which contribute to learning problems ( Eisenberg et al., 2010 ). Unfortunately, these difficulties tend to be common in preschool and kindergarten. They are an important determinant of whether educators and parents regard young children as “ready for school” ( Rimm-Kaufman et al., 2000 ).

Some researchers also suggest that emotion regulation in preschool and kindergarten serves as an early indicator of later academic success ( Graziano et al., 2007 ; Howse et al., 2003b ; Trentacosta and Izard, 2007 ). In preschool, McClelland and colleagues (2007) found not only that emotion regulation predicted early skills in literacy and mathematics but also that growth in emotion regulation in 4-year-olds over a 1-year period was linked to greater gains in literacy, vocabulary, and math compared with children showing less growth. Reading disability and problem behavior may be a “chicken or egg” problem: students who have behavior problems in first grade are more likely to have reading difficulties in third grade and students who have reading difficulties in first grade are more likely to exhibit behavior problems in third grade ( Morgan et al., 2008 ). Thus a particularly effective learning environment may be one that provides both effective reading instruction and support for behavioral self-regulation ( Connor et al., 2014 ).

Young children are better enabled to exercise self-regulation in the company of educators who have developmentally appropriate expectations for their self-control, provide predictable routines, and offer guidance that scaffolds their developing skills of self-management, especially in the context of carefully designed daily practices in a well-organized setting ( Bodrova and Leong, 2012 ). Indeed, in an intervention for academically at-risk young children, the Chicago School Readiness Project gave Head Start teachers specialized training at the beginning of the year in classroom management strategies to help lower-income preschoolers better regulate their own behavior. At the end of the school year, these children showed less impulsiveness, fewer disruptive behaviors, and better academic performance compared with children in classrooms with teachers who received a different training regimen ( Raver et al., 2009 , 2011 ).

Conclusion About the Ability to Self-Regulate The ability to self-regulate both emotion and cognitive processes is important for learning and academic achievement, affecting children's thinking, motivation, self-control, and social interactions. Children's progress in this ability from birth through age 8 is influenced by the extent to which relationships with adults, learning environments, and learning experiences support this set of skills, and their progress can be impaired by stressful and adverse circumstances.

Social and Emotional Understanding

As described earlier in this chapter, even infants and toddlers have an implicit theory of mind for understanding how certain mental states are associated with people's behavior. From their simple and straightforward awareness that people act intentionally and are goal directed; that people have positive and negative feelings in response to things around them; and that people have different perceptions, goals, and feelings, young children develop increasingly sophisticated understanding of the mental experiences that cause people to act as they do ( Wellman, 2011 ). They realize, for example, that people's beliefs about reality can be accurate or may be mistaken, and this realization leads to their understanding that people can be deceived, that the child's own thoughts and feelings need not be disclosed, and that not everybody can be believed ( Lee, 2013 ; Mills, 2013 ). They appreciate that people's thinking may be biased by expectations, prior experiences, and desires that cause them to interpret the same situation in very different ways ( Lalonde and Chandler, 2002 ). They also begin to appreciate how personality differences among people can cause different individuals to act in the same situation in very different ways ( Heyman and Gelman, 1999 ).

These remarkable advances in social understanding are important to children's developing socioemotional skills for interacting with educators and peers. These advances also are fostered by children's classroom experiences. Children learn about how people think and feel from directly observing; asking questions; and conversing about people's mental states with trusted informants, such as parents ( Bartsch and Wellman, 1995 ; Dunn, 2002 ; Thompson et al., 2003 ). Similarly, interactions with educators and peers provide young children with apt lessons in mutual understanding and perspective taking, cooperation, conflict management, personality differences and similarities, and emotional understanding in an environment where these skills are developing. This is especially so when educators can use children's experiences as forums for developing social and emotional understanding, such as when they explain why peers are feeling the way they do, suggest strategies for resolving conflict over resources or a point of view, or involve children in collective decision making involving different opinions.

Self-Awareness and Early Learning

How young children think of themselves as learners, and in particular their self-perceived efficacy in mastering new understanding, is an early developing and continuously important influence on their academic success. Young children become increasingly sensitive to the positive and negative evaluations of their behavior by parents, which serve as the basis for their self-evaluations ( Stipek et al., 1992 ). In one study, mothers who provided positive evaluations, gentle guidance, and corrective feedback during teaching tasks with their 2-year-olds had children who, 1 year later, were more persistent and less likely to avoid difficult challenges. By contrast, mothers who were intrusively controlling of their toddlers had children who, 1 year later, responded with shame when they had difficulty ( Kelley et al., 2000 ). Gunderson and colleagues (2013) found that 14- to 38-month-old children whose parents praised their efforts during unstructured home observations were more likely, as third graders, to believe that abilities are malleable and can be improved.

An extensive research literature documents the effects of parents' and educators' performance feedback on children's self-concept and motivation to succeed. Most of this research was conducted with older children and adolescents because of their more sophisticated understanding of differences in ability (see Wigfield et al., 2006 , for a review); however, preschoolers and early primary grade students are also sensitive to success and failure and to their imputed causes. In a study by Cimpian and colleagues (2007) , for example, 4-year-old children were represented by puppets whose performance was praised by a teacher using either generic feedback (“You are a good drawer.”) to imply trait-based (ability-centered) success or nongeneric feedback (“You did a good job drawing.”) to imply situation-based (effort-centered) success. The children did not differ in their self-evaluations after hearing praise of either kind, but when their puppet subsequently made a mistake and was criticized for it, the 4-year-olds who had heard generic feedback evaluated their performance and the situation more negatively than did children hearing nongeneric feedback, suggesting that they interpreted criticism as reflecting deficits in their ability. Similar results have been reported with kindergarteners by Kamins and Dweck (1999) and by Zentall and Morris (2010) , with the latter indicating that task persistence as well as self-evaluation were strengthened by the use of nongeneric performance feedback.

Parent and educator expectations for children's academic success also are important influences. High parental expectations for children's school achievement are associated with children's later academic performance, and this association often is mediated by the greater involvement of parents in the preschool or school program and other practices that support children's school success ( Baroody and Dobbs-Oates, 2009 ; Englund et al., 2004 ; Mantzicopoulos, 1997 ). The role of educator expectations in children's success is illustrated by a longitudinal study in which teacher expectations for children's math achievement in grades 1 and 3 directly predicted children's scores on standardized achievement tests 2 years later; teacher expectations for reading achievement had indirect associations with later reading scores. The results of this study also suggest that teacher expectations were especially influential for academically at-risk students ( Hinnant et al., 2009 ).

Social Interaction as a Forum for Cognitive Growth

A wider perspective on the importance of socioemotional skills for academic success is gained by considering the importance of social experiences for early learning. Contemporary research has led developmental scientists to understand the mind's development as deriving jointly from the child's naturally inquisitive activity and the catalysts of social experience. Sometimes these social experiences are in formal teaching and other pedagogical experiences, but often they take the form of adults and children sharing in activities that provide the basis for early learning, in a kind of “guided participation” (e.g., Rogoff, 1991 ). These activities can be as simple as the one-sided “conversation” parents have with their infant or toddler from which language skills develop, or the shared sorting of laundry into piles of similar color, or labeling of another child's feelings during an episode of peer conflict. In short, considerable early learning occurs in the course of a young child's ordinary interactions with a responsive adult.

Social experiences provide emotional security and support that enables learning and can also contribute to the development of language, number skills, problem solving, and other cognitive and learning skills that are foundational for school readiness and academic achievement. Through their interactions with children, adults provide essential stimulation that provides rapidly developing mental processes with catalysts that provoke further learning. Conversely, the lack of these catalysts contributes to learning disparities by the time that children become preschoolers. These processes are well illustrated by considering the growth of language and literacy skills and of mathematical understanding.

It is difficult to think of any child developing language apart from social interactions with others. As discussed earlier in this chapter, variability in these experiences, beginning in infancy, helps account for socioeconomic disparities in language and mathematical skills that are apparent by the time children enter school. In a widely cited study, Hart and Risley (1995) recorded 1 hour of naturally occurring speech in the homes of 42 families at monthly intervals beginning when children were 7-9 months old and continuing until they turned 3 years. They found that by age 3, children living in the most socioeconomically advantaged families had a working vocabulary that was more than twice the size of that of children growing up in the most disadvantaged families. The latter group of children also was adding words more slowly than their advantaged counterparts. The differences in children's vocabulary size were associated, in part, with how many words were spoken to them during the home observations, with a much richer linguistic environment being characteristic of the most advantaged homes. In addition, words were used in functionally different ways, with a much higher ratio of affirmative-to-prohibitive language being used in the most advantaged homes and a much lower ratio (i.e., below 1) being characteristic of the most disadvantaged homes. Differences in the language environment in which children grew up were, in other words, qualitative as well as quantitative in nature. Further research with a subset of 29 families in this sample showed that 3-year-olds' vocabulary size significantly predicted their scores on standardized tests of language skill in third grade ( Hart and Risley, 1995 ).

A later study by Fernald and colleagues (2013) confirms and extends these findings. A sample of 48 English-learning infants from families varying in socioeconomic status was followed from 18 to 24 months. At 18 months, significant differences between infants from higher- and lower-income families were already seen in vocabulary size and in real-time language processing efficiency. By 24 months, a 6-month gap was found between the two groups in processing skills related to language development. A companion study by Weisleder and Fernald (2013) with 29 lower-income Spanish-speaking families found that infants who experienced more child-directed speech at 19 months had larger vocabularies and greater language processing efficiency at 24 months. But adult speech that was simply overheard by infants (i.e., not child directed) at 19 months had no association with later language ( Schneidman et al., 2013 ). These studies indicate that child-directed speech, and perhaps the social interaction that accompanies it, is what strengthens infants' language processing efficiency. As in the Hart and Risley (1995) study, differences in family language environments were both qualitative and quantitative in nature. These findings are important in light of the association between the socioeconomic status of children's families and their language skills ( Bradley and Corwyn, 2002 ).

The findings of these studies are consistent with those of studies of the social experiences in and outside the home that promote language learning in early childhood. (See also the section on language and literacy under “Learning Specific Subjects” earlier in this chapter.) According to one longitudinal study, language and literacy skills in kindergarten were predicted by several aspects of the language environment at home and in classrooms in the preschool years. The characteristics of adult language that stimulated young children's language development included adult use of varied vocabulary during conversations with children; extended discourse on a single topic (rather than frequent topic switching); and diversity of language-related activities, including storybook reading, conversation related to children's experiences and interests, language corrections, and pretend play ( Dickinson, 2003 ; Dickinson and Porche, 2011 ; Dickinson and Tabors, 2001 ). These elements of the early childhood social environment predicted both kindergarten language skills and fourth-grade language and reading abilities. Other studies show that extensive use of descriptive language (e.g., labeling and commenting on people's actions) related to the child's current experience contributes to the quality of children's language development. Shared storybook reading also has been found to enhance the language skills of young children in lower-income homes ( Raikes et al., 2006 ). Stated differently, what matters is not just how much language young children are exposed to but the social and emotional contexts of language shared with an adult.

Language and literacy development is a major focus of instruction in prekindergarten and K-3 classrooms, and the instructional strategies used by teachers are both more formal and more sophisticated than those used in early childhood classrooms. Duke and Block (2012) have noted that in primary grade classrooms, vocabulary, reading comprehension, and conceptual and content knowledge are not adequately emphasized. The practices that would enhance early reading skills are embedded in children's social experiences with educators and peers in the classroom. They involve children interacting with partners throughout reading activity, and teachers explaining and discussing vocabulary terms and encouraging children to make personal connections with the concepts in the text.

Number Concepts and Mathematics

Language and literacy skills are the best-studied area in which early social experiences are influential, but they are not the only skills for which social interactions are important. Social experiences also are important for mathematics, such as for developing an understanding of numbers as well as early number and spatial/geometric language. Infants have an approximate number system that enables them to distinguish different quantities provided that the numerical ratio between them is not small, and this discrimination ability improves with increasing age (see Box 4-5 earlier in this chapter). There is some evidence that early individual differences in this ability are consistent during the first year and predict later mathematical abilities, although the reason for this remains unclear ( Libertus and Brannon, 2010 ; Starr et al., 2013 ). Toddlers also are beginning to comprehend certain number principles, such as one-to-one correspondence ( Slaughter et al., 2011 ). How adults talk about number is important. In one study, everyday parent–child discourse was recorded for 90 minutes every 4 months when the child was between 14 and 30 months old. The amount of parents' spontaneous “number talk” in these conversations (e.g., counting objects, references to time) was predictive of children's cardinal number knowledge (i.e., the knowledge that “four” refers to sets with four items) at 46 months ( Levine et al., 2010 ). Particularly important was when parents counted or labeled fairly large sets of objects within the child's view, providing concrete referents for parent–child interaction over number ( Gunderson and Levine, 2011 ).

Klibanoff and colleagues (2006) found that in early childhood, teachers' “math language”—that is, the frequency of their verbal references to number and geometric concepts—varied greatly for different teachers, but it significantly predicted progress in preschoolers' mathematical knowledge over the course of the school year. Similarly, another study found that parents' number-related activities at home with their young children were highly variable, but parents who engaged in more of these activities had children with stronger mathematical skill on standardized tests ( Blevins-Knabe and Musun-Miller, 1996 ). These practices in the classroom and at home help explain the significant socioeconomic disparities in number understanding by the time children arrive at school ( Klibanoff et al., 2006 ; Saxe et al., 1987 ). In addition to spoken references to numerical and geometric concepts, adults stimulate developing mathematical understanding when they incorporate these concepts into everyday activities, including games and other kinds of play; prompt children's explanations for numerical inferences; probe their understanding; and relate mathematical ideas to everyday experience ( NRC, 2009 ). Unfortunately, the quality of mathematical instruction is highly variable in preschool and early primary grades (discussed further in Chapter 6 ).

Taken together, these studies suggest the diverse ways in which social experiences provide catalysts for children's developing language and number skills that are the focus of later academic work. In these domains, adult practices provide essential cognitive stimulants beginning in infancy. Similar practices—adapted to young children's developing skills—remain important as children proceed through the primary grades.

Relationships and Early Learning: Implications for Adults

The relationship of an adult to a child—the emotional quality of their interaction, the experiences they have shared, the adult's beliefs about the child's capabilities and characteristics—helps motivate young children's learning, inspire their self-confidence, and provide emotional support to engage them in new learning.

Commonplace interactions provide contexts for supporting the development of cognitive and learning skills and the emotional security in which early learning thrives. Applauding a toddler's physical skills or a second-grader's writing skills, counting together the leaves on the sidewalk or the ingredients of a recipe, interactively reading a book, talking about a sibling's temper tantrum or an episode of classroom peer conflict—these and other shared experiences contribute to young children's cognitive development and early learning.

Conclusion About Socioemotional Development Socioemotional development contributes to the growth of emotional security that enables young children to fully invest themselves in new learning and to the growth of cognitive skills and competencies that are important for learning. These capacities are essential because learning is inherently a social process. Young children's relationships—with parents, teachers, and peers—thus are central to the learning experiences that contribute to their later success.

• PHYSICAL DEVELOPMENT AND HEALTH

Child development and early learning are closely intertwined with child health. Indeed, each is a foundation for outcomes in the other: health is a foundation for learning, while education is a determinant of health ( Zimmerman and Woolf, 2014 ). The Center on the Developing Child at Harvard University (2010) has described three foundational areas of child health and development that contribute to physical and mental well-being:

• Stable and responsive relationships—Such relationships provide young children with consistent, nurturing, and protective interactions with adults that enhance their learning and help them develop adaptive capacities that promote well-regulated stress response systems.
• Safe and supportive physical, chemical, and built environments—Such environments provide physical and emotional spaces that are free from toxins and fear, allow active exploration without significant risk of harm, and offer supports for families raising young children.
• Sound and appropriate nutrition—Such nutrition includes health-promoting food intake as well as eating habits, beginning with the future mother's nutritional status even before conception.

This section examines interrelated topics of physical development, child health, nutrition, and physical activity and then touches on partnerships between the health and education sectors (also discussed in Chapter 5 ).

Physical Development

Physical development goes hand-in-hand with cognitive development in young children, and progress in one domain often relies on progress in the other. Similar to cognitive development, typical physical development follows a common trajectory among children but with individual differences in the rate of development. A child's physical development encompasses healthy physical growth; the development of sensory systems, including vision and hearing; and development of the ability to use the musculoskeletal system for gross motor skills that involve large body movements as well as fine motor skills that require precision and the controlled production of sound for speaking. Sensory and motor development are critical for both everyday and classroom activities that contribute to cognitive development, early learning, and eventually academic achievement.

Young children's growth in gross and fine motor skills develops throughout the birth through age 8 continuum—early on from holding their head up; rolling over; standing, crawling, and walking; to grasping cereal, picking up blocks, using a fork, tying shoelaces, and writing. A number of recent studies have focused on the relationships among the development of fine and gross motor skills in infants and young children, cognitive development, and school readiness. For example, one study found that students showing deficiencies in fine motor skills exhibited lower math and verbal scores ( Sandler et al., 1992 ), and more recent studies have also shown that fine motor skills were strongly linked to later achievement ( Grissmer et al., 2010a ; Pagani and Messier, 2012 ). Some of the same neural infrastructure in the brain that controls the learning process during motor development are also involved in the control of learning in cognitive development ( Grissmer et al., 2010a ). The evidence of the impact of motor skills on cognitive development and readiness for school calls for a shift in curricula to include activities that focus on fine motor skills, to include the arts, physical education, and play ( Grissmer et al., 2010b ).

Child Health

Health has an important influence on early learning and academic achievement. Hair and colleagues (2006) found that poor health can be as important in contributing to struggles with academic performance in first grade as language and cognitive skills, along with lack of social skills. Not only are healthy children better prepared to learn, but participation in high-quality early childhood programs leads to improved health in adulthood, setting the stage for intergenerational well-being. Data from Head Start and from the Carolina Abecedarian Project indicate that high-quality, intensive interventions can prevent, or at least delay, the onset of physical and emotional problems from adolescence into adulthood ( Campbell et al., 2014 ; Carneiro and Ginja, 2012 ). Data from a national longitudinal survey show that involvement in Head Start was associated with fewer behavior problems and serious health problems, such as 29 percent less obesity in males at 12 and 13 years of age. In addition, Head Start participants had less depression and obesity as adolescents and 31 percent less involvement in criminal activity as young adults. Similarly, long-term follow-up of adults who were enrolled in the Carolina Abecedarian Project revealed that males in their mid-30s in the project had lower rates of hypertension, obesity, and metabolic syndrome than controls. None of the males in the project had metabolic syndrome, compared with 25 percent of the control group. Further analysis of growth parameters indicated that those who were obese in their mid-30s were on that trajectory by 5 years of age, indicating the need for emphasis on healthy nutrition and regular physical activity beginning in early childhood. These studies suggest that the impact of early care and education programs on physical and emotional health is long term.

Sufficient, high-quality dietary intake is necessary for children's health, development, and learning. Support for providing healthy nutrition for children and their families, including pregnant and expectant mothers, is vital. Adequate protein, calories, and nutrients are needed for brain development and function. While the rapid brain growth and development that occurs in infants and toddlers may make children in this age group particularly vulnerable to dietary deficiencies, nutrition remains important as certain brain regions continue to develop through childhood into adolescence.

Nutrients, Cognitive Development, and Academic Performance

Deficiencies in protein, energy, and micronutrients such as iron, zinc, selenium, iodine, and omega-3 fatty acids have been linked to adverse effects on cognitive and emotional functioning ( Bryan et al., 2004 ). Research has shown that iron-deficiency anemia (IDA) is associated with lower cognitive and academic performance ( Bryan et al., 2004 ; Nyaradi et al., 2013 ; Taras, 2005 ). Children at an early school age who had IDA as an infant were found to have lower test scores than those who did not have IDA. Effects of severe IDA in infancy have been seen in adolescence. These effects include lower scores in motor functioning; written expression; arithmetic achievement; and some specific cognitive processes, such as spatial memory and selective recall ( NRC and IOM, 2000 ). However, it is not clear whether children with iron deficiency but no anemia have similar outcomes ( Taras, 2005 ). A review of daily iron supplementation in children aged 5-12 years studied in randomized and quasi-randomized controlled trials showed improvement in measures of attention and concentration, global cognitive scores, and, for children with anemia, intelligence quotient (IQ) scores ( Low et al., 2013 ).

IDA in infancy also has been associated with impaired inhibitory control and executive functioning. Altered socioemotional behavior and affect have been seen in infants with iron deficiency regardless of whether anemia is present ( Lozoff, 2011 ). One study found an association between iron supplementation in infancy and increased adaptive behavior at age 10 years, especially in the areas of affect and response to reward, which may have beneficial effects on school performance, mental health, and personal relationships ( Lozoff et al., 2014 ).

Folate and iodine also have been shown to be important for brain development and cognitive performance ( Bougma et al., 2013 ; Bryan et al., 2004 ; Nyaradi et al., 2013 ), although iodine deficiency is rare in the United States. While there is some evidence that zinc, vitamin B 12 , and omega-3 polyunsaturated fatty acids also may be important for cognitive development, the research on these associations is inconclusive ( Bougma et al., 2013 ; Bryan et al., 2004 ; Taras, 2005 ).

Food Insecurity, Diet Quality, and Healthful Eating

Food insecurity and diet quality in children have both been linked to impaired academic performance and cognitive and socioemotional development. Food insecurity refers to circumstances in which households do not have adequate food to eat, encompassing both inadequate quantity and nutritional quality of food ( ERS, 2014 ). Food insecurity affects development not only by compromising nutrition but also by contributing to a factor in family stress ( Cook and Frank, 2008 ). In 2012, 48 million Americans were food insecure, a fivefold increase from the 1960s and a 57 percent increase from the late 1990s. One in six Americans reported being short of food at least once per year. More than half of affected households were white, and more than half lived outside cities. Indeed, hunger in the suburbs has more than doubled since 2007. Two-thirds of food-insecure households with children have at least one working adult, typically in a full-time job ( McMillan, 2014 ).

A recent review indicates that food insecurity is a “prevalent risk to the growth, health, cognitive, and behavioral potential of low-income children” ( Cook and Frank, 2008 , p. 202). Studies found that children in food-insufficient families were more likely than those in households with adequate food to have fair/poor health; iron deficiency; and behavioral, emotional, and academic problems. Infants and toddlers are at particular risk from food insecurity even at its least severe levels ( Cook and Frank, 2008 ). Cross-sectional studies of children from developing countries have shown an association among general undernutrition and stunting, IQ scores, and academic performance ( Bryan et al., 2004 ). Alaimo and colleagues (2001) found that food insecurity was linked to poorer academic and psychosocial outcomes in children ages 6 to 11 years. Similarly, Florence and colleagues (2008) observed that students with lower overall diet quality were significantly more likely to fail a literacy assessment. Subsequent research has shown that while food insecurity experienced earlier in childhood was associated with emotional problems that appeared in adolescence, cognitive and behavioral problems could be accounted for by differences in the home environments, such as family income and the household's sensitivity to children's needs ( Belsky et al., 2010 ).

Eating breakfast, which can be related to food insecurity, diet quality, and healthful eating habits, has been associated with improved cognitive function, academic performance, and school attendance ( Basch, 2011 ; Hoyland et al., 2009 ; Mahoney et al., 2005 ; Nyaradi et al., 2013 ; Rampersaud et al., 2005 ). According to two reviews of the effect of consuming breakfast in children and adolescents, the evidence suggests that children who consume breakfast—particularly those children whose nutritional status is compromised—may have improved cognitive function, test grades, and school attendance. The positive effects of school breakfast programs may be explained in part by their effect of increasing school attendance ( Hoyland et al., 2009 ; Rampersaud et al., 2005 ). The composition of the breakfast meal may also be important to cognitive performance; a breakfast meal with a low glycemic index, such as oatmeal, has been shown to improve cognitive function ( Cooper et al., 2012 ; Mahoney et al., 2005 ).

In 2011, the Centers for Disease Control and Prevention (CDC) published a report documenting the relationship between healthy eating and increased life expectancy; improved quality of life; and fewer chronic diseases, including cardiovascular disease, obesity, metabolic syndrome, diabetes, and inadequate bone health ( CDC, 2011 ). The report documents the high rate of iron deficiency among obese children and emphasizes the link between dental caries and unhealthy diet. Children are unlikely to follow recommendations for the number of servings of various food groups and they consume higher-than-recommended amounts of saturated fats, sodium, and foods with added sugar. Children's eating behavior and food choices are influenced not only by taste preferences but also by the home environment and parental influences, including household eating rules, family meal patterns, and parents' lifestyles. The school environment influences children's eating behavior as well. The availability of unhealthy options in schools leads to poor choices by children, whereas research has shown that efforts to reduce the availability of sugar-sweetened beverages in the schools can have a positive impact on children's choices ( AAP Committee on School Health, 2004 ). There are also rising concerns about food insecurity in association with obesity; inexpensive foods tend not to be nutritious, and contribute to increasing rates of obesity ( IOM, 2011 ; McMillan, 2014 ).

Physical Activity

A recent Institute of Medicine (IOM) study linked increasing physical activity and enhancing physical fitness to improved academic performance, and found that this can be facilitated by physical activity built into children's days through physical education, recess, and physical classroom activity ( IOM, 2013 ). Likewise, the American Academy of Pediatrics recently highlighted the crucial role of recess as a complement to physical education, suggesting that recess offers cognitive, social, emotional, and physical benefits and is a necessary component of a child's development ( AAP Council on School Health, 2013 ). However, fewer than half of youth meet the current recommendation of at least 60 minutes of vigorous- or moderate-intensity physical activity per day, and recent years have seen a significant downward trend in the offering of daily physical education in schools at all levels ( CDC, 2012 ; GAO, 2012 ). Positive support from friends and family encourages children to engage in physical activity, as do physical environments that are conducive to activity. However, the school environment plays an especially important role. The IOM report recommends that schools provide access to a minimum of 60 minutes of vigorous- or moderate-intensity physical activity per day, including an average of 30 minutes per day in physical education class for students in elementary schools ( IOM, 2013 ).

Partnerships Between Health and Education

Each of the domains of child development and early learning discussed in this chapter can be supported through interventions that involve both the health and education sectors (see also the discussion of continuity among sectors in Chapter 5 ). Specific activities include coordinating vision, hearing, developmental, and behavioral screening to facilitate early identification of children with special needs; completing daily health checks; making appropriate referrals and collaborating with the child's medical home and dental health services; ensuring that immunizations for the entire family and for the early care and education workforce are up to date; modifying and adapting services to meet the individual needs of the child; and providing support to the early care and education workforce to promote more inclusive practices for children with special needs. In addition, teaching and modeling skills in sanitation and personal hygiene will contribute to preventing illness. Furthermore, pediatric health care professionals can make an important contribution by promoting literacy. Extensive research documents the positive impact on early language and literacy development when a pediatric professional gives advice to parents about reading developmentally appropriate books with children as early as 6 months of age ( AAP Council on Early Childhood et al., 2014 ).

There is evidence that coordinated efforts between educational settings and health care services lead to improved health. Head Start, the Infant Health and Development Program, and the Carolina Abecedarian Project are examples of early care and education programs that have integrated health care services into the intervention design, leading to positive health outcomes. Schools also can partner with pediatric health care professionals in their communities to identify opportunities to enhance physical activity in the school setting ( AAP Committee on Sports Medicine and Fitness and AAP Committee on School Health, 2000 ). CDC (2011) has offered recommendations for promoting healthful eating and physical activity that include the following and, if placed in an appropriate developmental context, can be applied to care and education settings for children aged 0-8:

• Use a coordinated approach to develop, implement, and evaluate healthful eating and physical activity policies and practices.
• Establish school environments that support healthy eating and activity.
• Provide a quality school meal program and ensure that students have only appealing, healthy food and beverage choices offered outside of the school meal program.
• Implement a comprehensive physical activity program with quality physical education as the cornerstone.
• Implement health education that provides students with the knowledge, attitudes, skills, and experiences needed for healthy eating and physical activity.
• Provide students with health, mental health, and social services to address healthy eating, physical activity, and related chronic disease prevention.
• Partner with families and community members in the development and implementation of healthy eating and physical activity policies, practices, and programs.
• Provide a school employee wellness program that includes healthy eating and physical activity services for all school staff members.
• Employ qualified persons and provide them with professional development opportunities in staffing physical education; health education; nutrition services; health, mental health, and social services; and supervision of recess, cafeteria time, and out-of-school-time programs.

School-based health centers are another approach to partnering between health and education. They have been associated with improved immunization rates, better adherence to scheduled preventive examinations, and more treatment for illnesses and injuries, as well as fewer emergency room visits. For example, King and colleagues (2006) found that a school-based vaccination program significantly reduced influenza symptoms in the entire school. School-based mental health services also have been shown to be effective in addressing a wide range of emotional and behavioral issues ( Rones and Hoagwood, 2000 ). School-based health centers have been shown to reduce nonfinancial barriers to health care ( Keyl et al., 1996 ), and families also report more satisfaction with their care than in community or hospital settings ( Kaplan et al., 1999 ).

Conclusion About Health, Nutrition, and Early Learning Safe physical and built environments, health, and nutrition are essential to early learning and academic achievement. Food security and adequate nutrition are important to support cognitive development and participation in education, and food insecurity and poor nutrition can contribute to early learning difficulties. Care and education settings provide an opportunity to promote healthful eating and physical activity in learning environments. Providing appropriate health and developmental screenings and follow-up care and services also is important in supporting development and early learning.

Health and Early Learning: Implications for Adults

Healthy children supported by healthy adults are better prepared to learn. Child health begins prior to conception and extends through pregnancy and throughout childhood. Therefore, the early care and education workforce must be prepared to work across generations to provide education, support, and community linkages to ensure that children grow up poised for success. Ongoing federal support for evidence-based home visiting programs for high-risk families that begin early in pregnancy and continue through early childhood is essential. Professionals working in family childcare, early childhood education centers, preschools, and early elementary schools need to have working knowledge of the relationship between health and children's learning and development. Guidance related to nutrition, physical activity, oral health, immunizations, and preventive health care is essential across all early care and education settings. These professionals also need to be provided with supports and opportunities for close collaboration with health care services and their potential integration into or strengthened linkages with the early care and education setting.

• EFFECTS OF CHRONIC STRESS AND ADVERSITY

As detailed in Chapter 3 , one of the most important advances in developmental science in recent years has been the recognition that the brain incorporates experience into its development. Although experience is important at any age, early experiences are especially formative in the development of the brain's structure and function. Human development is the result of the continuous interaction of genetics and experience. This interplay is true not just of brain development but of other aspects of human development as well. Research in this area encourages developmental scientists as well as parents and practitioners to consider how positive early experiences and enrichment, in formal and informal ways, may have a beneficial influence on the developing brain and in turn on the growth of thinking and learning. The brain's openness to experience is, however, a double-edged sword—adverse early experiences can have potentially significant negative consequences for brain development and early learning.

As discussed in Chapter 3 , evidence indicates that experiences of stress and adversity are biologically embedded and that individual differences exist in the health and developmental consequences of stress. A substantial body of evidence now shows that adversity and stress in early life are associated with higher rates of childhood mental and physical morbidities, more frequent disturbances in developmental trajectories and educational achievement, and lifelong risks of chronic disorders that compromise health and well- being ( Boyce et al., 2012 ; Hertzman and Boyce, 2010 ; Shonkoff et al., 2009 ). Children respond to stress differently. Many exhibit withdrawal, anger and irritability, difficulty paying attention and concentrating, disturbed sleep, repeated and intrusive thoughts, and extreme distress triggered by things that remind them of their traumatic experiences. Some develop psychiatric conditions such as depression, anxiety, posttraumatic stress disorder, and a variety of behavioral disorders ( NCTSN, 2005 ).

What are the circumstances that contribute to chronic adversity and stress for children? All children can experience forms of chronic stress and adversity, but exposures to stress and adversity are socioeconomically layered. Poverty, discussed in more detail below, has been the best studied and is a highly prevalent source of early chronic stress ( Blair and Raver, 2012 ; Evans and Kim, 2013 ; Jiang et al., 2014 ). Young children in the United States also suffer high levels of victimization through child abuse and exposure to domestic violence. The U.S. Department of Health and Human Services reported for the year 2012 that of all child abuse victims, approximately 60 percent were age 8 or younger ( Children's Bureau, 2013 ). The highest rates of child abuse and neglect, including fatalities related to child abuse, were reported for children in the first year of life. Comparable biological and behavioral effects of chronic stress have been studied in children in foster care, in those who experience significant or prolonged family conflict, in those who have a depressed parent, and in those who are abused or neglected (see Thompson, 2014 , for a review).

It is noteworthy that these circumstances include not only those that most people would regard as sources of extreme stress for children (e.g., child abuse), but also those that an adult might regard as less significant because they may be less severe although persistent (e.g., parents' chronic marital conflict, poverty). This broader range of circumstances that children experience as stressful is consistent with the view that, in addition to situations that are manifestly threatening and dangerous, children are stressed by the denial or withdrawal of supportive care, especially when they are young.

Culture also is closely interrelated with stress and adversity. Culture affects the meaning that a child or a family attributes to specific types of traumatic events as well as the ways in which they respond. Because culture also influences expectations regarding the self, others, and social institutions, it can also influence how children and families experience and express distress, grieve or mourn losses, provide support to each other, seek help, and disclose personal information to others. Historical or multigenerational trauma also can influence cultural differences in responses to trauma and loss ( NCTSN Core Curriculum on Childhood Trauma Task Force, 2012 ).

Building on the discussion in Chapter 3 of the biology of chronic stress and adversity, the following sections describe more broadly some of the contributing circumstances and consequences for young children, including the stressors associated with economic adversity; social buffering of stress; and the relationships among stress, learning, and mental health.

The Stressors of Economic Adversity

Children in any economic circumstances can experience stress and adversity, but considerable research on the effects of chronic stress on children's development has focused on children living in families in poverty or with low incomes. The number of children in these conditions of economic adversity is considerable. In 2012, nearly half the children under age 6 lived in poverty or low-income families (defined as up to 200 percent of the federal poverty level, 2 which remains a meagre subsistence) ( Jiang et al., 2014 ). During that same year, more than half the children living with their families in homeless shelters were under the age of 6 ( Child Trends, 2015 ).

The research is clear that poverty as a form of early chronic adversity is a risk factor to long-term physical and mental health, and that for children it can be a significant threat to their capacities to cope with stress, socialize constructively with others, and benefit from the cognitive stimulating opportunities of an early childhood classroom. Socioeconomic disparities in children's experiences of socioemotional adversity and challenging physical environments are well documented (see, e.g., Evans et al., 2012 ). Factors other than economic status itself contribute to the challenges and stresses for children living in low-income families ( Fernald et al., 2013 ). Poverty often is accompanied by the confluence of multiple sources of chronic stress, such as food insufficiency, housing instability (and sometimes homelessness), exposure to violence, environmental noise and toxins, dangerous neighborhoods, poor childcare and schools, family chaos, parents with limited capacity (e.g., resources, education, knowledge/information, time, physical or mental energy) to be supportive and nurturing, parents who are anxious or depressed, parents who are harsh or abusive caregivers, impoverished parent–child communication, and home environments lacking cognitively stimulating activities ( Evans et al., 2012 ; Fernald et al., 2013 ).

As discussed in detail in Chapter 3 , the perturbed biological processes that often accompany economic adversity include changes in the structure and function of children's brain circuitry and dysregulation of their central stress response systems. For these children, therefore, the effects of the chronic stresses associated with economic adversity are likely to contribute to academic, social, and behavioral problems. These problems affect not only early learning and the development of cognitive skills (with impacts on the development of language being best documented) but also the development of learning skills associated with self-regulation and persistence, as well as coping ability, health, and emotional well-being ( Blair and Raver, 2012 ; Evans and Kim, 2013 ).

In addition, developmental consequences related to socioeconomic status are not seen exclusively in children from severely impoverished families. Rather, evidence shows a graded effect of deprivation and adversity across the entire spectrum of socioeconomic status, with even those children from the second-highest social class showing poorer health and development compared with those from families of the very highest socioeconomic status ( Adler et al., 1994 ; Hertzman and Boyce, 2010 ). Moreover, as discussed in Chapter 3 , children are not equally affected by early adverse experiences. Genetic and epigenetic influences may have a role in whether some children are more resilient to early adversity than others ( Rutter, 2012 ).

Detrimental prenatal influences may also be important ( Farah et al., 2008 ; Hackman et al., 2010 ). Although this report focuses on children beginning at birth, child development and early learning also are affected by what a child is exposed to before birth, including influences of family disadvantage. Box 4-6 highlights major research findings on the relationships among family disadvantage, fetal health, and child development.

Family Disadvantage, Fetal Health, and Child Development. Children from different family backgrounds—affected by systemic inequities and disadvantage—start life with starkly different health endowments. As but one example, having a low-birth-weight (more...)

Social Buffering of Stress

The neuroscience of stress has yielded greater understanding of how the effects of stress may be buffered through social support. In behavioral and neurobiological studies of humans and animals, researchers have shown how individuals in adversity show diminished behavioral reactivity and better-regulated cortisol response, among other effects, in the company of people who provide them with emotional support. For children, these individuals often are attachment figures in the family or outside the home.

In health psychology, the benefits of social support for the development and maintenance of healthy practices and the control of disease pathology and healing have been studied since the 1970s (e.g., Cassel, 1976 ; Cobb, 1976 ). Social support also has been recognized as a contributor to psychological well-being for children and youth in difficult circumstances ( Thompson and Goodvin, in press) . In recent years, research on the neurobiology of the social buffering of stress has contributed to a better understanding of why social support has these benefits ( Hostinar et al., 2014 ). In human and animal studies, social companionship in the context of adversity appears to have effects on the biological regulators of hypothalamic–pituitary–adrenal (HPA) activity, contributing to greater regulation of stress reactivity through cortical and limbic influences. Social support also appears to stimulate the down-regulation of the proinflammatory tendencies induced by chronic stress, as well as processes driven by neurohormones, including oxytocin, that have other positive benefits ( Kiecolt-Glaser et al., 2010 ). Stated differently, social support not only counters the negative effects of chronic stress reactivity but also stimulates constructive influences that contribute independently to greater self-regulation and well-being ( Hostinar et al., 2014 ). This research is still at an early stage, and establishing reliable associations between brain and behavioral functioning in this area is a work in progress, but research findings are providing increasing support for these processes. In one study, for example, greater maternal support measured when children were preschoolers predicted children's larger hippocampus volume at school age ( Luby et al., 2012 ).

The potential benefits of social support as a buffer of chronic stress reactivity underscore the plasticity of developing behavioral and biological systems. Children in adversity need not suffer long-term harms arising from the effects of chronic stress exposure. In a study of families living in rural poverty, for example, toddlers' chronic exposure to domestic violence was associated with elevated cortisol reactivity. However, this effect was buffered when mothers were observed to respond sensitively to their children ( Hibel et al., 2011 ). Experimental interventions designed to change stressful circumstances and promote positive relationships have yielded similar findings. For example a program aimed at easing young children's transition to new foster care placements and promoting warm, responsive, and consistent relationships with new foster parents provided individualized sessions with child therapists, weekly playgroup sessions, and support for foster parents. This program resulted in a normalization of the children's HPA hyporesponsiveness (an effect of stress discussed in Chapter 3 ) ( Fisher et al., 2007 , 2011 ). Another example comes from an intervention based on attachment theory, which trained caregivers to better interpret and respond affectionately to infants and toddlers in foster care and similarly resulted in a normalization of HPA activity and lower cortisol reactivity ( Dozier et al., 2006 , 2008 ). There may be limits to these potential ameliorative effects, depending on the severity and duration of the exposure to adversity. Children who lived for an extended period in profoundly depriving Romanian orphanages, for example, did not show recovery of dysregulated cortisol reactivity, even after a prolonged period of supportive adoptive care ( Gunnar et al., 2001 ).

Because interventions that can help children recover from the effects of chronic adversity can be expensive and time-consuming, however, it appears sensible to try to prevent these effects from occurring. This can be accomplished by reducing exposure to influences that cause significant stress for children, and by strengthening supportive relationships that can buffer its effects. The development of warm, secure attachments between parents and children illustrates the latter approach. As discussed earlier in this chapter, attachment theorists argue that the reliable support provided by a secure attachment relationship enables infants and children to explore and learn from their experiences confidently with the assurance that a trusted adult is available to assist if difficulty ensues. In this view, secure attachments buffer stress and significantly reduce the child's need to be vigilant for threat or danger. As noted previously, attachment research documents a range of benefits associated with secure parent–child relationships in childhood, including greater language skill, academic achievement, and social competence (see Thompson, 2008 , for a review; West et al., 2013 ). The view that these accomplishments are explained, at least in part, by how secure attachments buffer stress for children is supported by studies documenting the better-regulated cortisol reactivity of young children with secure attachments in challenging situations (see Gunnar and Donzella, 2002 , for a review; Nachmias et al., 1996 ).

Viewed in this light, it appears that the contributions adults make to children's learning extend significantly beyond their reading, conversing, counting, and providing other direct forms of cognitive stimulation. An essential contribution is the safety and security they provide that not only buffers children against significant stress when this occurs, but also enables children to invest themselves in learning opportunities with confidence that an adult will assist them when needed. Such confidence not only enables children to learn more from the opportunities afforded them in the family and outside the home but also fosters their developing self-confidence, curiosity, and other learning skills that emerge in the context of secure relationships ( Thompson, 2008 ). This is a benefit of secure, warm adult–child relationships for all children, not just those in adverse circumstances. This phenomenon is perhaps analogous to that seen in studies in which rat pups with nurturant mothers show enhanced learning and memory in low-stress contexts, whereas pups with nonnurturant mothers show greater proficiency in fear conditioning ( Champagne et al., 2008 ).

One problem, however, is that children in adverse circumstances usually have parents and other caregivers who are affected by the same conditions of adversity. Thus, their parents may not be able to provide them with the support they need. This realization has led to the growth of two-generation interventions that are designed to assist children by providing support to their parents in difficult circumstances ( Chase-Lansdale and Brooks-Gunn, 2014 ).

Stress, Learning, and Mental Health

Children learn readily in contexts of social support and emotional well-being, which derive from positive relationships with those who care for and educate them in the family and outside the home. In these contexts, adults can support and encourage developing competencies, convey positive values about learning and school, and help instill curiosity and self-confidence in children. By contrast, learning and cognitive achievement are hindered when children are troubled. This is the case for children from infancy through adolescence who are living in homes with significant marital conflict, when mothers are chronically depressed, when parents are hostile and coercive, or in other circumstances of family turmoil (e.g., Bascoe et al., 2009 ; Brennan et al., 2013 ; Canadian Paediatric Society, 2004 ; Davies et al., 2008 ).

Socioemotional hindrances to learning and cognitive achievement are apparent very early, before children have begun school, and continue to be important as children move into the primary grades. In educational settings, the emotional effects of problems in educator–child relationships can undermine children's performance and their academic success ( Hamre and Pianta, 2004 ; Jeon et al., 2014 ; Pianta, 1999 ; Pianta and Stuhlman, 2004b ; Skinner and Belmont, 1993 ). As discussed in Chapter 3 , when children are in circumstances of chronic or overwhelming stress, stress hormones affect multiple brain regions, including those relevant to learning, attention, memory, and self-regulation ( McEwen, 2012 ; Ulrich-Lai and Herman, 2009 ). Over time and with continued exposure to stressful circumstances, these neurocognitive processes become altered as a result of the progressive wear and tear of stress hormones on biological systems as they adapt to this chronic stress. As a consequence, immunologic capacities become weakened (contributing to more frequent acute and chronic illness), self-regulation is impaired (contributing to poorer emotion regulation and impulse control), and cognitive and attentional capabilities are blunted ( Danese and McEwen, 2012 ; Lupien et al., 2009 ; Miller et al., 2011 ). For children, these effects can help account for problems in following instructions, paying attention, managing impulsivity, focusing thinking, and controlling emotions in social encounters—each of which can impair classroom performance and academic achievement.

Young children's vulnerability to stress and their reliance on the support of adults are two central considerations in understanding the foundations for childhood mental health ( IOM and NRC, 2009 ). This relationship among stress, early development, and mental health is relevant to understanding the influences that can threaten the socioemotional well-being of younger children—and to understanding why behavior problems can undermine learning and cognitive growth. One illustration of these effects is the high rates of preschool and prekindergarten children being expelled from their classrooms because of disruptive behavior problems—by one report at a rate more than three times the rate of children in the K-12 grades ( Gilliam, 2005 ; see also U.S. Department of Education Office for Civil Rights, 2014 ). In this study, the likelihood of expulsion decreased significantly when educators were provided access to early childhood mental health consultants who could assist them in managing behavior problems.

Another illustration is reports by kindergarten teachers that social, emotional, and self-regulatory problems are a common impediment to children's readiness to achieve in their classrooms ( Lewit and Baker, 1995 ; Rimm-Kaufman et al., 2000 ). Other studies have shown that children's conduct problems and internalizing (anxious, depressed) behavior in the classroom can undermine the development of constructive educator–child relationships and foreshadow later social and academic difficulties ( Berry and O'Connor, 2010 ; Koles et al., 2009 ; Ladd and Burgess, 2001 ).

Consistent with the research concerning the biological and behavioral effects of chronic stress, there is increasing evidence that even very young children show clear evidence of traumatization and posttraumatic stress, anxious and depressive symptomatology, behavioral and conduct problems, and other serious psychological problems ( Egger and Angold, 2006 ; Lieberman et al., 2011 ; Luby, 2006 ; Zeanah, 2009 ). Sometimes these symptom patterns overlap, such as in the comorbidity in which depressive symptomatology appears along with oppositional behavior in preschoolers ( Egger and Angold, 2006 ). The origins of these problems are multifaceted, but certainly include interaction of environmental stresses with genetic factors that heighten or reduce children's vulnerability to these stresses. Often these environmental stresses undermine the social support that would otherwise buffer the effects of stress on children. Diagnosing these disorders in young children is a challenge because the behaviors associated with early mental health problems in young children can be different from those observed in adults and adolescents ( Egger and Emde, 2011 ). But progress has been made in developing reliable diagnostic criteria for preschoolers (e.g., Egger and Angold, 2006 ; Keenan et al., 1997 ; Lavigne et al., 2009 ) and even infants and toddlers ( Zero to Three, 2005 ). This work provides a foundation for further study of the developmental origins of early mental health challenges and therapeutic interventions that might help these children.

Connecting the Socioemotional Health of Children and Adults

The preceding discussion makes clear that children's socioemotional health is linked to the socioemotional well-being of the adults in their lives. Consistent with the research on the social buffering of stress discussed earlier, when parents and other caregivers are managing well, they can help children cope more competently with the ordinary stresses that inevitably occur. When caregivers are stressed, by contrast, they cannot provide this buffering and are instead more often a source of stress for children. When parents are depressed, for example, they can be unpredictably sad, hostile, critical, and/or disengaged ( NRC and IOM, 2009 ). This constellation of behaviors constitutes a difficult combination of threat and withdrawal of support for children. Young children with a depressed mother are more likely, therefore, to exhibit heightened stress reactivity to moderate challenges; to have an insecure attachment to the parent; to show lower levels of cognitive performance and, later, poorer academic achievement; and to be at greater risk of becoming depressed themselves.

The adult's emotional well-being is important in the classroom as well. Using data from the Fragile Families and Child Wellbeing study, Jeon and colleagues (2014) measured the depressive symptomatology of 761 home- and center-based care providers, as well as overall observed classroom quality, and obtained independent measures of the behavior problems of the 3-year-olds in their classrooms. They found that educator depression was linked to higher levels of behavior problems in children, attributable to the poorer quality of the classroom environment. Notably, this study was conducted with a sample of families in economic stress, with the educators often sharing the same financial difficulties. Nevertheless, the association of educator depression with child behavior problems remained even when family influences, including maternal depression and family poverty status, were controlled for. Similar associations of educator well-being with the quality of the classroom environment and children's learning have been found in studies of children in the early primary grades (e.g., Pianta, 1999 ; Pianta and Stuhlman, 2004b ).

Conclusions About Chronic Stress and Adversity Chronic stress and adversity constitute fundamental risks to learning and academic success as well as to emotional well-being for many young children. The biological and behavioral effects of stress and adversity can disrupt brain circuitry and stress response systems, affect fundamental cognitive skills, undermine focused thinking and attention, diminish self-regulation, and imperil mental and physical health. Trauma, adversity, and chronic stress can arise from many sources, such as poverty, family conflict, parental depression, abuse, neglect, or exposure to violence in the community. Supportive and stable relationships with adults can help develop children's adaptive capacities and provide them with a significant stress buffer. It is important for adults who work with children to recognize and appreciate the effects of adversity and to have the capacity to employ strategies for preventing or mitigating them, as well as for promoting cognitive, social, and emotional strengths for coping with adverse and stressful experiences. Given the importance of stable and responsive relationships that provide consistent and nurturing interactions, the well-being of the adults who care for young children contributes to their healthy development and early learning. The stresses of economic disadvantage are manifested not only in differences in children's early experiences in the family and the community but also in the quality and stability of the out-of-home care and education families can access and afford and the quality of the schools children later attend. Socioeconomic differences in the quality of early learning opportunities place large numbers of children at a learning disadvantage and undermine their potential for academic success. These differences begin early and have a cumulative effect over time. Strengthening early learning and developing competencies requires serious and sustained attention to these socioeconomic disparities in opportunity.

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An ongoing study and forthcoming report of the Institute of Medicine and the National Research Council focuses on research, practice, and policy for young dual language learners. More information about this study can be found at www ​.iom.edu/English-DualLanguageLearners .

The 2012 federal poverty threshold was $23,364 for a family of four with two children, $18,480 for a family of three with one child, $15,825 for a family of two with one child.

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InBrief: The Science of Early Childhood Development

This brief is part of a series that summarizes essential scientific findings from Center publications.

Content in This Guide

Step 1: why is early childhood important.

• : Brain Hero
• : The Science of ECD (Video)
• You Are Here: The Science of ECD (Text)

Step 2: How Does Early Child Development Happen?

• : 3 Core Concepts in Early Development
• : 8 Things to Remember about Child Development
• : InBrief: The Science of Resilience

Step 3: What Can We Do to Support Child Development?

• : From Best Practices to Breakthrough Impacts
• : 3 Principles to Improve Outcomes

The science of early brain development can inform investments in early childhood. These basic concepts, established over decades of neuroscience and behavioral research, help illustrate why child development—particularly from birth to five years—is a foundation for a prosperous and sustainable society.

Brains are built over time, from the bottom up.

The basic architecture of the brain is constructed through an ongoing process that begins before birth and continues into adulthood. Early experiences affect the quality of that architecture by establishing either a sturdy or a fragile foundation for all of the learning, health and behavior that follow. In the first few years of life, more than 1 million new neural connections are formed every second . After this period of rapid proliferation, connections are reduced through a process called pruning, so that brain circuits become more efficient. Sensory pathways like those for basic vision and hearing are the first to develop, followed by early language skills and higher cognitive functions. Connections proliferate and prune in a prescribed order, with later, more complex brain circuits built upon earlier, simpler circuits.

The interactive influences of genes and experience shape the developing brain.

Scientists now know a major ingredient in this developmental process is the “ serve and return ” relationship between children and their parents and other caregivers in the family or community. Young children naturally reach out for interaction through babbling, facial expressions, and gestures, and adults respond with the same kind of vocalizing and gesturing back at them. In the absence of such responses—or if the responses are unreliable or inappropriate—the brain’s architecture does not form as expected, which can lead to disparities in learning and behavior.

The brain’s capacity for change decreases with age.

The brain is most flexible, or “plastic,” early in life to accommodate a wide range of environments and interactions, but as the maturing brain becomes more specialized to assume more complex functions, it is less capable of reorganizing and adapting to new or unexpected challenges. For example, by the first year, the parts of the brain that differentiate sound are becoming specialized to the language the baby has been exposed to; at the same time, the brain is already starting to lose the ability to recognize different sounds found in other languages. Although the “windows” for language learning and other skills remain open, these brain circuits become increasingly difficult to alter over time. Early plasticity means it’s easier and more effective to influence a baby’s developing brain architecture than to rewire parts of its circuitry in the adult years.

Cognitive, emotional, and social capacities are inextricably intertwined throughout the life course.

The brain is a highly interrelated organ, and its multiple functions operate in a richly coordinated fashion. Emotional well-being and social competence provide a strong foundation for emerging cognitive abilities, and together they are the bricks and mortar that comprise the foundation of human development. The emotional and physical health, social skills, and cognitive-linguistic capacities that emerge in the early years are all important prerequisites for success in school and later in the workplace and community.

Toxic stress damages developing brain architecture, which can lead to lifelong problems in learning, behavior, and physical and mental health.

Scientists now know that chronic, unrelenting stress in early childhood, caused by extreme poverty, repeated abuse, or severe maternal depression, for example, can be toxic to the developing brain. While positive stress (moderate, short-lived physiological responses to uncomfortable experiences) is an important and necessary aspect of healthy development, toxic stress is the strong, unrelieved activation of the body’s stress management system. In the absence of the buffering protection of adult support, toxic stress becomes built into the body by processes that shape the architecture of the developing brain.

Policy Implications

• The basic principles of neuroscience indicate that early preventive intervention will be more efficient and produce more favorable outcomes than remediation later in life.
• A balanced approach to emotional, social, cognitive, and language development will best prepare all children for success in school and later in the workplace and community.
• Supportive relationships and positive learning experiences begin at home but can also be provided through a range of services with proven effectiveness factors. Babies’ brains require stable, caring, interactive relationships with adults — any way or any place they can be provided will benefit healthy brain development.
• Science clearly demonstrates that, in situations where toxic stress is likely, intervening as early as possible is critical to achieving the best outcomes. For children experiencing toxic stress, specialized early interventions are needed to target the cause of the stress and protect the child from its consequences.

Suggested citation: Center on the Developing Child (2007). The Science of Early Childhood Development (InBrief). Retrieved from www.developingchild.harvard.edu .

Related Topics: toxic stress , brain architecture , serve and return

Explore related resources.

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Reports & Working Papers : From Best Practices to Breakthrough Impacts

Briefs : InBrief: The Science of Neglect

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Reports & Working Papers : The Science of Neglect: The Persistent Absence of Responsive Care Disrupts the Developing Brain

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Analyzing early child development, influential conditions, and future impacts: prospects of a German newborn cohort study

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The paper provides an overview of a German cohort study of newborns which includes a representative sample of about 3500 infants and their mothers. The aims, challenges, and solutions concerning the large-scale assessment of early child capacities and skills as well as the measurements of learning environments that impact early developmental progress are presented and discussed. First, a brief overview of the German regulations related to early child education and care (ECEC) and parental leave as well as the study design are outlined. Then, the assessments of domain-specific and domain-general cognitive and socio-emotional indicators of early child functioning and development are described and the assessments of structural, orientational, and process quality of the children’s learning environment at home and in child care are presented. Special attention is given to direct assessments and their reliability and validity; in addition, some selected results on social disparities are reported and the prospects of data analyses are discussed.

Early childhood and early child education are an important basis for later development, educational performance, and pathways as well as for lifelong learning and well-being. This important claim has been made repeatedly (Caspi et al. 2003 ; Noble et al. 2007 ), and even critical phases of development have been suggested (e.g., Mayberry et al. 2002 ). Nevertheless and despite the existence of quite a few longitudinal studies addressing this issue, empirical evidence concerning effective conditions, differential child progress, and how the early phases of life impact future development and prospects is still rare.

From an educational and political point of view, it is alarming that various studies have documented profound disparities in child development according to family background when children are merely 3 years of age (Brooks-Gunn and Duncan 1997 ; Dubowy et al. 2008 ; Hart and Risley 1995 , 1999 ; Weinert et al. 2010 ). Even in the first year of life, very early roots of social disparities have been demonstrated which increased substantially over the next few years (Halle et al. 2009 ). In addition, some studies show a high stability of interindividual differences and social disparities from age three onward across preschool (Weinert and Ebert 2013 ; Weinert et al. 2010 ) and school age (Law et al. 2014 ). Notably, the stability of individual differences in children’s test performance has been shown to be even more pronounced in educationally dependent domains of development, like language and factual knowledge, than in more domain-general and less culture-dependent facets of children’s cognitive functioning, as indicated by non-verbal intelligence test scores (Weinert et al. 2010 ).

Drawing on a bioecological model of development (Bronfenbrenner and Morris 2006 ), developmental progress and child education are influenced from early on by the interaction between (developing) child characteristics, skills, and competencies and the quality of structural and process characteristics of the learning environment at the child’s home (Bakermans-Kranenburg and van Ijzendoorn 2011 ; Bradley and Corwyn 2002 ; Ebert et al. 2013 ; Weinert et al. 2012 ) as well as in child care (Anders et al. 2013 ). Longitudinal studies shed light on these interactions and how they impact later development and education, which is of great importance for gaining a better understanding of the underlying processes and influential conditions. It is important to note that the form and organization of the various learning environments are affected by state regulations, which differ between countries, resulting in different support systems, offers and regulations for parents from child birth until her/his formal school enrolment (Waldfogel 2001 ).

Regulations in Germany

Maternity leave regulations in Germany prescribe a period of 14 weeks for maternity leave which is divided into two phases: 6 weeks before and 8 weeks after birth. Mothers receive maternity pay from public funds in addition to their employer’s contribution which amounts to 100 % of their former income. After this period, parents are offered various options for taking parental leave until the child’s third birthday. Specifically, parents may interrupt their employment to provide child care and are legally protected from dismissal during this 3-year period; parents also receive parental pay during their parental leave (substitution of income) amounting to two-thirds of her/his prior salary (ranging from € 300.- up to € 1800.-) for a maximum period of 14 months.

Governments also support families through child care policies. The German early child education and care (ECEC) system covers institutional care and education before and alongside elementary and secondary school. Since 1993 children from age of three onward have had a legal right to institutional child care which is primarily organized by local communities and welfare organizations providing care to mainly age-mixed groups at centers with varying opening hours (Linberg et al. 2013 ). However, during the last decade, there has been growing demand for ECEC for children under the age of three that led to the enactment of laws on the demand-driven expansion of child care (“Tagesbetreuungsausbaugesetz TAG”) and the expansion of child care infrastructure for infants and children (“Kinderförderungsgesetz KiföG”) in 2005 and 2008, respectively. Additionally, the legal right to institutional ECEC was expanded in 2013 to include 1-year-old children and political leaders from local, state, and federal levels agreed to provide enough places for 35 % of the children.

Accordingly, the actual use of child care for young children under the age of three has rapidly changed during recent years: Within 8 years (2005–2013), the child care rates for the under 3-year olds increased from 7 to 23 % in the Western states of Germany and from 36 to 47 % in the Eastern states, which have their own distinct tradition and infrastructure concerning early care and education (Kreyenfeld and Krapf 2016 ). In 2015, the nation-wide care rate amounted to 32.9 % with mean values of 28.2 % for the Western and 51.9 % for the Eastern states (Statistisches Bundesamt 2016 ).

However, despite rising rates of early education, a child’s family still is the first and often only environment for developmental processes during the first years of life. Thus, there is a substantial need for analyzing the decision mechanisms as well as the effects of the various options available for early child care.

To summarize, longitudinal studies that provide a basis for analyzing the conditions which significantly contribute to early developmental progress are of great importance for the individual child as well as for society. These studies produce relevant knowledge on how children’s abilities, skills, and competencies develop based on individual resources and conditions; how learning opportunities influence their development in different contexts; how disparities emerge early in life; and how all this impacts educational careers, lifelong learning, well-being, and participation in society.

The German National Educational Panel Study

(NEPS) Footnote 1 has been set up to substantially contribute to these issues (Blossfeld et al. 2011 ). The idea of a multicohort panel study was brought up by the German Federal Ministry of Education and Research (BMBF). A nation-wide interdisciplinary scientific network of researchers was established to develop this idea further and to prepare a proposal for a longitudinal representative large-scale educational study to investigate, monitor, and compare competence development and educational processes in Germany. In light of the specific challenges associated with sampling and measurement of early child characteristics, a newborn cohort study was not initially included in the main NEPS program, but was planned to be conducted as an associated add-on project. However, the study was incorporated into the NEPS study design on behalf of the international evaluation committee organized by the German Research Foundation (DFG) for two main reasons: the growing research on the importance of early child development and education and the rapid changes taking place in early child care, including new social policies being implemented in Germany (see above).

The NEPS is carried out by a network of excellence. It features a longitudinal multicohort sequence design and comprises more than 60,000 target persons as well as 40,000 context persons. In particular, the NEPS design encompasses six longitudinal panel studies conducted simultaneously, which cover a wide range of ages and educational stages. NEPS data are disseminated in a user-friendly way to the scientific community. According to the sensitivity of data, the access is given by a web download, a remote access solution, or on-site in a secure environment. All data are documented in English and are available for use by national and international researchers. In addition to providing substantial analyses of the data themself, it can be used as a benchmark for intervention research, international comparison, and for evaluating issues such as the differences and changes in the use of institutional child care.

At the moment, more than 1100 researchers from more than 700 projects are drawing on the NEPS data already published. The data are used for research in a variety of scientific disciplines and also for educational monitoring—especially, the indicator-based National Report for Education. In order to facilitate access to results for a wide range of professions interested in education—including policy, administration, and practice—scientific papers with important conclusions and empirical evidence are currently summarized by the Leibniz Institute for Educational Trajectories (LIfBi) for public communication and information beyond science and are distributed via the NEPS webpage. Moreover, results are regularly fed back to these groups by presentations and newsletters.

The present paper provides an overview of the NEPS newborn cohort study and its analytic potential. First, the design of the study will be presented with a special emphasis on the aims, challenges, and solutions for the assessment of child characteristics and learning environments. We will then report a few selected results (a) concerning the validity and reliability of the measures used and (b) on early social disparities.

Design of the newborn cohort study of the NEPS: a brief overview

Like all other cohort studies of the NEPS, the cohort study of newborns addresses five research perspectives (Blossfeld et al. 2011 ). Drawing on a theoretical framework, various domain-specific as well as domain-general indicators of early child capacities, characteristics, and developments are assessed as well as measures of structural and process characteristics of their (different) learning environments and their social, occupational, and educational family background. In addition, there is a special focus on families with a migration background, on educational decisions (e.g., concerning child care), and—especially in the newborn cohort study—on patterns of coparenting and child care arrangements. By combining direct observational measures, interview data, and questionnaires, the newborn cohort study allows for in-depth analyses of developmental progress and influential conditions that affect the development of educationally relevant competencies and the stability or changes of interindividual differences. Therefore, it provides insight into the mechanisms through which social disparities emerge, change, and impact children’s future prospects and returns to education.

Sampling strategy

To ensure a representative sample, a two-stage procedure was implemented: 84 German municipalities were used as primary sampling units, explicitly stratified according to three strata of urbanization (via the number of inhabitants; see Aßmann et al. 2015 ). Within these municipalities, addresses were sampled and divided into two birth tranches (infants born between February and April 2012 and between May and June 2012) in order to guarantee a small age range for the infant sample. Starting from a gross sample of about 8500 families, a total of about 3500 families (response rate 41 %) took part in the first assessment wave. In the second wave, the realized sample still included about 2850 families (panel stability 83 %).

Assessment waves and data collection

During the very early phases of child development, three successive assessment waves were carried out when children were on average 7 months (wave 1), 17 months (wave 2), and 26 months of age (wave 3). In the first and third wave video-taped observations and computer-assisted personal interviews (CAPI) were conducted at the family’s home for the entire sample. In the second wave, families were surveyed by computer-assisted telephone interviews (CATI), while video-taped observational measures at the child’s home were only assessed in half of the sample (subsample approx. 1500) in accordance with the study’s design. After wave 3 (i.e., from age two onward) children and their context persons were and will be surveyed every year. Data are collected by trained interviewers. Mothers are the primary respondents, as they can provide valid information about conditions and feelings during and after their pregnancy. Each assessment wave is preceded by a longitudinal pilot study, which runs 1 year before the main study is conducted, to test all instruments and procedures.

Measuring early child characteristics: aims, challenges, and solutions

The assessment of a child’s capacities, characteristics, and early development is pivotal for analyzing the effects of environmental conditions and the impact of early child development and education on later development, educational achievement, career, and life satisfaction or other outcomes and returns. In particular, measuring child characteristics is essential to the modeling of intra-individual progress and changes in interindividual differences, including the emergence of social disparities in various domains of development across childhood. At the same time, it is crucial for analyzing the mechanisms of change, the effects of learning environments and opportunities, and their interactions with the individual capacities and characteristics of the children, while taking the risk or protecting factors of the individual child and his/her environment into account, as well as for controlling for basic interindividual differences if necessary.

However, measuring early child characteristics is a major challenge for longitudinal studies, especially large-scale studies. This is due to various issues and questions, such as which aspects and indicators of early child development should be assessed, how should they be measured, and how can the standardization and validity of measurements be ensured in large-scale assessments of very young children.

Early child development: domain-specific challenges for the child

Developmental psychology has convincingly documented for a long time that neither the development of children nor the development of infants is a homogeneous endeavor. Since the time of Piaget’s ( 1970 ) overarching stage theory of development, it has been empirically demonstrated that development is domain-specific, i.e., demands, prerequisites, effective environmental stimulations differ according to the developmental domain under study (e.g., the acquisition of language, of mathematical competencies, of competencies in natural science, or of an intuitive psychology) (Karmiloff-Smith 1999 ). Even in infancy domain-specific precursors of e.g., mathematical and psychological knowledge and competencies are observable (Goswami 2008 ). Determining how educationally relevant competencies emerge from the interplay of these domain-specific precursors and domain-general basic capacities of the child (like basic reasoning abilities, speed of information processing, or executive functions including cognitive flexibility, inhibition, working memory) on the one hand and of the environmental conditions in the family and in child care on the other is an important issue to be addressed by educational studies. It is important to note that (interindividual differences in) basic capacities also change with age and environmental conditions, although not to the same extent as culture- and education-dependent competencies, and that stimulation of and progress in one developmental domain may enhance, hinder, or compensate for those in other domains.

General NEPS framework for assessing competencies

Within the NEPS, a general framework for assessing educationally relevant abilities and competencies has been developed (Weinert et al. 2011 ). Specifically, the assessments include (a) domain-general cognitive abilities/capacities captured by the constructs of “fluid intelligence” (Cattell 1971 ) or “cognitive mechanics” (Baltes et al. 2006 ); these refer to performance differences in speed of basic cognitive processes, the capacity of working memory, and the ability to apply deductive or analogical thinking in new situations (Brunner et al. 2014 ); (b) domain-specific cognitive competencies, e.g., language competencies, mathematical competencies, and natural science competencies are to be assessed longitudinally and as coherently as possible; and not least (c) meta-competencies, including self-regulation (in the cognitive, behavioral, and emotional domain) and socio-emotional competencies are to be measured (see Weinert et al. 2011 for an elaborated rational of the assessments).

Selecting and measuring relevant and predictive indicators of early child development: a challenge for research

As already mentioned, even in infancy and early childhood, there is no overall indicator for children’s capacities and development. Considering the fact that there are thousands of studies into infant competencies, the indicators have to be carefully selected—not least because of the limited study time and other constraints associated with large-scale assessments, especially those concerning infants and young children who cannot be tested in group settings and whose attentional capacities are still limited. Within the NEPS, the selection draws on the general framework outlined above, including domain-general basic capacities, domain-specific precursors and early roots of language and mathematics as well as indicators of socio-emotional development and early self-regulation.

However, deciding on how to measure these early child characteristics and developments is a major challenge for theoretically sound educational large-scale assessments. Just relying on parents’ reports is problematic since the parents’ judgements might be affected, for example, by their (different) knowledge of child development, by possible restrictions/differences in how they observe the child, and by their particular cultural and individual beliefs and biases. In addition, major aspects of domain-general and domain-specific cognitive functioning and development are not easily observable and need sophisticated assessment methods developed in infancy research.

If newborn cohort studies took direct measures into consideration in addition to interviews and questionnaires, they often relied on the Bayley Scales of Infant Development (Bayley 2006 ; Schlesiger et al. 2011 for a brief overview). However, the NEPS feasibility and pilot studies revealed that the standardized administration of test items (using an educationally sound selection of items) turned out to be highly error-prone for trained interviewers who are usually experts in administering interviews but not tests. In addition, the sensorimotor indicators of developmental status measured by the Bayley Scales have been shown to be rather instable across situations (Attig et al. 2015 ) and infancy (McCall et al. 1977 ) and were hardly predictive for later cognitive functioning (e.g., Fagan and Singer 1983 ). Therefore, an indicator of basic information processing abilities was introduced within the NEPS newborn cohort study which has predominantly been used in baby lab studies, namely, the children’s visual attention and speed of habituation within a habituation–dishabituation paradigm. Within this paradigm, the child’s visual attention and the decrease of her/his visual attention when being presented with a series of identical or categorically similar stimuli are used as indicators of the child’s ability to build up a cognitive representation of a stimulus or a stimulus category (Pahnke 2007 ; Sokolov 1990 ). In addition, a new stimulus (or a stimulus from a new category) is presented in the dishabituation phase of the paradigm and a new increase of the child’s visual attention is interpreted as a signal of her/his ability to distinguish stimuli or categories presented during the two phases of the paradigm and to show a preference toward new information. These measures have been shown to be highly predictive of later intelligence scores or other indicators of cognition and language (Bornstein and Sigman 1986 ; Fagan and Singer 1983 ; Kavšek 2004 ). Thus, this paradigm was used to assess early domain-general information processing/categorization abilities; it was also used to measure early precursors of numeracy and word learning (see Table  1 ). To assure standardization and reliability, pictures were presented on a computer screen and the child’s looking behavior (look at/away from the respective stimulus) was video-taped (as were all other direct measures) and coded afterward on a 30 frames per second basis. A third direct indicator of early child characteristics relevant to learning and education is her/his interactional behavior (cognitive, behavioral, and socio-emotional aspects) in mother–child interaction (see “ Assessment of mother–child interaction: direct measurement of the home-learning environment and of the child’s characteristics in mother–child interaction ” section). Table  1 summarizes the measurements of child characteristics and development assessed in the first three waves of the NEPS newborn cohort study.

In addition to direct assessment, mothers were asked (see Table  1 ) about the child’s skills and development as well as about the child’s health. The questions on the child’s skills and development cover items on cognition (e.g., means-end task and object categorization), communicative gesture (e.g., to draw someone’s attention, negation/headshaking), gross and fine motor skills (e.g., climbing up steps, stacking of toy blocks) as well as language (e.g., size of productive vocabulary, comprehension of short instructions). A short version of the Infant Behavior Questionnaire (IBQ-R, Gartstein and Rothbart 2003 ) was used to assess facets of the child’s temperament, specifically orienting/regulatory capacity (items like “if you sing or speak to <target child’s name>, how often does she/he calm down instantly?”) and negative affectivity (items like “when <target child’s name> can’t have what she/he wants, how often does she/he get angry?”) (Bayer et al. 2015 ). In wave 3, a German language checklist and, for bilingual children, an additional Turkish or Russian language checklist (versions of the well-known MacArthur Communicative Development Inventory (CDI); Fenson et al. 1993 ) was introduced.

Measuring learning environments: aims, challenges, and solutions

Likewise, measuring learning environments that impact child development is an important challenge for longitudinal large-scale educational studies. As suggested by bioecological theories (Bronfenbrenner and Morris 2006 ), it is not enough to just focus on the home-learning environment; the use and features of non-parental care and other learning environments like parent–child programs, which 55 % of the children in the newborn cohort study experience in their first year of life, should also be assessed. Moreover, it is not sufficient to only measure quantitative structural characteristics, since domain-general and domain-specific qualitative aspects have been shown to be especially important (e.g., Anders et al. 2012 ; Sylva et al. 2006 ); however, indispensable direct observational measurements are hard to obtain in large-scale studies. It is important to note that the meaningfulness of the specific features/aspects assessed for characterizing the different learning environments and the constraints of the measurements have a large impact on the validity of subsequent analyses and conclusions.

General framework of the NEPS

To deal with these issues coherently across cohorts, the measurement of important characteristics of learning environments draws on a general framework which subdivides three different dimensions: Structural quality , which refers to relatively persistent general conditions; orientational quality , like values, norms, and attitudes of an actor; and process quality , which refers to the interaction of the individual with her/his learning environment (Bäumer et al. 2011 ).

Selection and measurement of indicators

For the assessment of the process quality of the home-learning environment as the central learning environment in the very early years, the NEPS newborn cohort study relies on both interviews/questionnaires and direct observations (see below).

In addition, as approx. 24 % of the children of the newborns’ cohort sample were using supplementary non-parental care settings in wave 2, the dimensions specified above were also surveyed in these child care settings using self-administered drop-off questionnaires for center-based ECEC as well as for child minders. Because the NEPS has to rely on survey data, the validity of the quality of non-parental care settings gained from the questionnaire is tested by conducting a sub-study, which compares observational methods with the questionnaire used in the NEPS study. The questionnaire covers structural characteristics as well as process characteristics (see Table  2 for examples).

Besides external day care, the newborn cohort study of the NEPS places a strong emphasis on the home-learning environment—especially in very early childhood—as it is of central importance for later development (NICHD 1998 ). Large-scale longitudinal studies mostly focus on the structural aspects of the home-learning environment to account for variability in infants’ and toddlers’ cognitive and social skills (Halle et al. 2009 ; Hillemeier et al. 2009 ). However, process variables account for additional variance in both social and cognitive child outcomes and may even mediate the effect of structural characteristics (Flöter et al. 2013 ; NICHD 1998 ). Therefore, the assessment of the home-learning environment is not only limited to measuring structural aspects like sociodemographics, but also includes orientations (see Table  3 ); in particular, special emphasis is given to the assessment of processes . Mothers are asked about issues, such as joint activities and their language use at home and the quality of these interactions is also assessed by means of videotaping mother–child interactions during the first three assessment waves (see Table  3 ; “ Assessment of mother–child interaction: direct measurement of the home-learning environment and of the child’s characteristics in mother-child interaction ” section).

Assessment of mother–child interaction: direct measurement of the home-learning environment and of the child’s characteristics in mother–child interaction

On the one hand, the assessment of mother–child interactions as a dyadic process allows a deeper look into maternal interaction behavior as a crucial characteristic of the home-learning environment; on the other hand, it captures additional information about the relevant characteristics of the child.

The quality of maternal interaction behavior has been shown to impact a child’s language (Nozadi et al. 2013 ; Tamis-LeMonda et al. 2001 ), cognitive (NICHD 1998 ; Pearson et al. 2011 ), and socio-emotional development (Bigelow et al. 2010 ; Meins et al. 2001 ). High-quality maternal interaction behavior in very early childhood is mostly described as interaction behavior that provides the child with emotional support in terms of sensitivity, which is defined as a prompt, warm, and contingent reaction to the child’s needs and signals (Ainsworth et al. 1974 ). But stimulating interaction behavior in the sense of scaffolding behavior (Wood 1989 ) is also regarded as high-quality maternal behavior, even in early childhood.

However, maternal interaction behavior cannot be considered separately from the child’s behavior, as interaction is a dyadic process in which both partners’ behavior refers to each other in a reciprocal way. It is well acknowledged that children play an active role in the dyadic interaction process from the very beginning, initiating interactions (van den Bloom and Hoeksma 1994 ) and influencing their occurrence and appearance (Lloyd and Masur 2014 ). Additionally, the child’s temperament (e.g., fear, excitement, protesting, and crying) can become effective in an interaction (Mayer 2013 ).

Accordingly, the NEPS newborn cohort study assesses maternal as well as filial interaction behavior via observation. The mother–child interactions are videotaped in the family home and are rated afterward by trained coders. The interaction itself takes place in a semi-standardized play situation in which the mother and the child play with a standardized toy set (Sommer et al. 2016 ). The play situation is adapted to the different age-related requirements: In the first wave, the mother–child interaction is videotaped for 5 min in which toys from the NEPS toy set are provided. In waves 2 and 3, the mother and child are observed while carrying out a three-bag procedure in which the mother and child played for 10 min with toys from three different bags in a set order (NICHD 2005 ).

Maternal as well as filial interaction behavior is assessed using a macro analytic rating system whereby various interactional characteristics are evaluated on five-point-rating scales with qualitatively specified graduations ([EKIE]; Sommer and Mann 2015 ). The assessment of maternal behavior covers emotional supportive interaction behavior (like sensitivity to distress and non-distress, positive regard for the child, emotionality) and stimulating interaction behavior, including a common rating for language and play stimulation in the first two waves and differentiating language and mathematical stimulation in wave 3 when children were 2 years of age (see Table  3 ). The mother’s intrusiveness, detachment, and negative regard of the child were also rated. The coding of the child’s behavior and emotions focuses on the child’s mood, activity level, social interest in the mother, and sustained attention to objects.

Some selected results

NEPS data are disseminated among the scientific community for analysis and provide an important basis for substantive longitudinal and comparative research. In particular, the various measurements of child characteristics and the detailed measures of the home-learning environment, including the observation of mother–child interactions, enable in-depth analyses to be conducted. In the first section, the results on the reliability and validity of these direct measures and information on the underlying constructs are given, while the second section contains an analysis of early social disparities in the mother’s behavior and child’s development. In addition to using the data from the newborn cohort study (wave 1), Footnote 2 we also draw on the data obtained from the “ViVA project,” Footnote 3 which aims to validate the NEPS measures as one of its objectives.

Reliability and validity of measures of mother–child interaction

Assessing interactions in a large-scale assessment is challenging with regard to validity and reliability of the measurements and ratings. In the NEPS newborn cohort study, these challenges were solved quite successfully: Weighted inter-rater reliability ranged from 84 to 100 % and the ecologic validity of the observed maternal interaction behavior seems to be high, as the data from the ViVA project show that interaction behavior assessed in the semi-structured play situation is comparable to maternal interaction behavior in other situations, i.e., natural feeding and diapering situations (Friedman test comparing differences between interaction situations: χ 2  = 0.74, p  = 0.69; Intra-Class-Correlations of maternal interaction behavior in different situations: ICC  = 0.68, p  < 0.001; n  = 23–30; Vogel et al. 2015 ).

Assessing the quality of the mother’s interaction behavior is a core construct of the home-learning environment in the first waves of the newborn cohort study and focuses on socio-emotional aspects as well as on stimulation. Although the assessed indicators address different aspects of maternal interaction behavior, some of them are related to each other (see Table  4 ). It is worth noting that aspects, like intrusiveness, detachment, or negative regard, are not simply the negative end of the more or less pronounced positive dimensions.

From a theoretical point of view, high-quality interaction behavior includes both sensitivity and stimulation behavior. To test the assumption that a rather broad composite indicator of quality of interaction behavior is not only theoretically but also empirically meaningful, a confirmatory factor analysis was conducted (see Fig.  1 ). Items in the socio-emotional domain ( sensitivity to non - distress , Footnote 4 positive regard , and emotionality ) as well as stimulation loaded substantially on quality of interaction behavior (all standardized coefficients above 0.45). Positive regard (0.69) and stimulation (0.77) contributed the most to this factor. Internal consistency was high (Cronbach's α = 0.80).

Results from confirmatory factor analysis for the latent variable Q uality of interaction behavior (Linberg et al. 2016 ). N  = 2190; Chi 2 (2) = 16.05, p  < .000; RMSEA  = 0.06; CFI  = .99; based on all German-speaking mother–child interactions in wave 1

One should note, however, that this broad measure of the quality of interaction behavior is only slightly, albeit significantly, related to other aspects of the home-learning environment which were assessed via the parents interview: This includes issues, like the overall amount of joint activities with the child ( r  = 0.13, p  < 0.000) and special activities (joint picture book reading, r  = 0.13, p  < 0.000; joint construction play, r  = 0.07, p  < 0.000; and talking to the child, r  = 0.07, p  < 0.000).

Reliability and validity of measures of early child characteristics

Given the sample size and household setting, the available data on child characteristics provide a rather detailed insight into the early stages of development, especially with respect to early cognitive capacities and child temperament, which are both measured by multiple indicators. As expected, the first results revealed that these multiple assessment approaches refer to different facets of early child development.

The mother’s report on the child’s temperament deals with the reactions of the child to stressful situations and her/his susceptibility to calming related behavior. In line with previous evidence, this is hardly related to the indicators of child’s temperament, which were assessed in a fairly relaxed mother–child interaction situation ( r  = 0.05, p  < 0.05; Freund and Weinert 2015 ). At the same time, there is evidence supporting the validity and reliability of these measurements. In the ViVA validation study, the information from the questionnaire has been shown to represent the complete subscales of the IBQ-R from which the items were selected ( r  = 0.51 for negative affectivity/0.70 for orienting/regulatory capacity, p  < 0.01; Bayer et al. 2015 ). In addition, it is correlated with the children’s reactions to stress-inducing maternal behavior in a still-face-paradigm where the mother is instructed not to react to her child’s signals ( r  = 0.34–0.43, p  < 0.05; Freund and Weinert 2015 ).

Likewise this can be shown for the assessments of early cognitive capacities/competencies. In the ViVA study, the items on sensorimotor development (assessment of developmental status) were highly correlated with the complete cognition and motor subscales of the Bayley Scales, respectively ( r  = 0.48–0.63, p  < 0.01; Attig et al. 2015 ). Hence the data on sensorimotor development as well as the data on basic information processing abilities (habituation–dishabituation paradigm; 85 % of the videos codable; non-completion of child <1 %; inter-coder reliability in wave 1: κ = 0.91) both rely on scientifically well-established and successfully applied assessments. Nevertheless, they are hardly correlated with each other and thus seem to cover different aspects of early development ( r  = 0.06/0.14, p  < 0.05; Weinert et al. 2016 ).

Although the findings always have to be considered within the context in which the assessments were made (e.g., short version/time), the validity of the various measurements of child characteristics and maternal interaction behavior seems to be apparent.

Early roots of social disparities in child development

The data of the NEPS newborn cohort study allow for an analysis of early social disparities with respect to both early child characteristics and their mother’s interaction behavior. Analyses of data from the first assessment wave when children were 6–8 months of age are in accordance with a bioecological model of child development (Weinert et al. 2016 ). As hypothesized, the mother’s interaction behavior in the video-taped mother–child interaction situation varied significantly according to her educational background. With regard to the broad concept of quality of interaction behavior described above, the mother’s education accounted—even in these early phases of child development—for 4 % ( p  < 0.001) of the variance within the German subgroup of participants. However, as expected we did not find substantial disparities in child characteristics in early childhood, like basic information processing abilities (habituation–dishabituation paradigm), developmental status (sensorimotor scale), or socio-emotional child characteristics coded during mother–child interaction. Interestingly, some early roots of social disparities were observed in child’s characteristics, such as sustained attention to objects and activity level in mother–child interaction. Notably, as predicted, mother–child interaction turned out to be a mutual endeavor: Interactional characteristics of the child (especially the child’s mood, her/his social interest, and continuing sustained attention to objects) and the child’s temperament (orienting/regulatory capacity) accounted for 29 % ( p  < 0.001) of the differences in the overall quality of the mother’s interaction behavior, over and above the control variables (age, sex) and socio-economic conditions (equivalized family income, education of mother, living in partnership) (Weinert et al. 2016 ). Of course, it is still an open question whether the differences observed between children result from former or actual differences in the mother’s behavior or whether the differences in child characteristics and behavior are effective in eliciting their mother’s behavior. In fact, the interrelation between mother and child behavior may vary according to other factors, e.g., additional protective or risk factors (Freund et al. 2016 ). Future findings from the NEPS cohort study of newborns will contribute to explaining how social disparities (suspected at age two and beyond) emerge, how they change over time, which mechanisms contribute to their emergence, and how they impact future development and education.

Prospects and conclusions

Insights and conclusions from longitudinal studies and analyses on the conditions which influence early developmental progress, the emergence of disparities, and their impacts are relevant to educational facilities and social policy and thus to the individual child as well as to society. The present paper focused on the first waves of a large-scale German cohort study of newborns. The various measures will help to better understand the stabilities, changes, and effects of qualitative and quantitative characteristics that early learning environments and other influential conditions have. They also illustrate how the very early outcomes of infant development act as a basis for future development. The child’s development will be measured by testing the development of mathematical, language, and early natural science competencies. Domain-general cognitive abilities will also be assessed (i.e., non-verbal categorization, delay of gratification, verbal memory, and executive functions) along with indicators of socio-emotional development (subscales of the Strength and Difficulties Questionnaire (SDQ), Goodman 1997 ), temperament (subscales of the Children’s Behavior Questionnaire (CBQ), Rothbart et al. 2001 ), and personality (BigFive; short version of the Five Factor Questionnaire for Children (FFFK); Asendorpf and van Aken 2003 ). Learning environments will be measured by interviews and questionnaires which draw on the general framework described above and will be supplemented with assessments of different facets of parenting style. To ensure standardization and reduce administration errors, all tests are carried out on tablet computers in child-oriented, playful settings.

It is worth noting that the kindergarten cohort of the NEPS, which started in 2010, also assessed comparable measures from age five onward. Here a sample of about 3000 children (institutional sample from 279 ECEC centers and 720 groups) was included. Despite differences between cohort designs (e.g., individual vs. institutional sample; child assessments at the children’s home vs. in preschool; playful test administration with vs. without tablet computers; CAPI vs. CATI interviews of the parents) the two cohort studies allow for comparisons while at the same time being characterized by partially complementary strengths and weaknesses (e.g., more elaborate information on home-learning environment vs. on institutional characteristics; extensive assessment of early roots vs. extensive assessment of further development). Among other things, this allows for an in-depth analysis of the interrelation between variations as well as an analysis of the constancies and changes in learning environments and child development, and it also relays important information concerning relevant aspects of early education and how it impacts development, educational career, and future prospects.

A better understanding of the relevant factors and conditions influencing early child development and learning together with their impact on children’s future development, educational success, and well-being is of special importance for ECEC policy. Longitudinal studies are needed because they allow analyses of the mechanism and processes of change in these decisive variables. While in cross-sectional studies causal effects cannot be inferred, longitudinal studies—especially those that enable complex group-specific growth-curve modeling and the modeling of intra-individual change—combined with experimental and quasi-experimental comparisons not only contribute significantly to gaining deeper insights into developmental and educational processes and the conditions influencing them but can also answer important questions relevant to ECEC policy such as how does early compared to late entry to institutional care impact later development in various cognitive and non-cognitive domains? Is early institutional care especially valuable (and to what extent) for different subgroups of children/families (e.g., disadvantaged families, children/families with specific risk factors, children with a migration background, refugees, multilingual children, e.g., children learning German as an (early) second or third language)? What are the determinants of the quality of home-learning environment and its effects on child development and education? What are specific risk (or protective) factors and is it possible to compensate for (or to draw on) them?

Obviously, even longitudinal studies will not deliver straightforward conclusions for ECEC policy. However, they provide an important and essential basis for evidence-based policy by informing about relevant conditions of early child education and how they impact later development (e.g., successful future development, educational drawbacks or opportunities in the social, socio-emotional, and cognitive domain). In fact, it has been suggested that high-quality early education is of special importance from a psychological, an educational, a sociological, and an economic perspective and thus is of significant relevance not only to the individual but also to society as a whole (Heckman 2013 ; Sylva et al. 2011 ). NEPS data are especially helpful when it comes to gaining a better understanding of the development of competencies and decisive conditions over the life course—the samples are carefully drawn, the validity of data is high, and longitudinal data are available in a user-friendly form for analyses and even for international comparisons.

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Authors’ contributions

SW conceptualized and drafted the overall manuscript, sequence alignment, and revisions. In addition she cooperatively conceived the design and assessments of the studies, in particular the assessment of early child competencies, and the analyses of social disparities. AL especially drafted the part on the learning environments and the assessment of mother-child interaction; she conducted the data analyses on mother-child interaction and supported the analyses on ecologic validity of mother-child-interaction. MA contributed to the description of the overall design and did the analyses on early roots of social disparities. She is also involved in the conceptualization and coordination of data assessment of the infant cohort study. TL drafted the part on regulations in Germany and contributed to the description of the assessment of learning environments. He is also involved in the conceptualization of the assessment of this data. JDF did the analyses on the reliability and validity of measures of early child characteristics; he drafted this part and cooperatively planned and conducted the validation study. All authors were involved in the sequence alignment and revisions, and approved the final manuscript. All authors read and approved the final manuscript.

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Weinert, S., Linberg, A., Attig, M. et al. Analyzing early child development, influential conditions, and future impacts: prospects of a German newborn cohort study. ICEP 10 , 7 (2016). https://doi.org/10.1186/s40723-016-0022-6

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DOI : https://doi.org/10.1186/s40723-016-0022-6

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During the process of development, a child transitions from being dependent on his parents to being an independent young adult. It is generally accepted that there are 5 main stages of child development: newborn, infant, toddler, preschool, and school-age.

If you are pursuing a bachelor of science or even a Master of Science degree, you will inevitably have to write at least one research paper about child development. The good news is that writing the paper shouldn’t be too difficult because the Internet contains plenty of information about most aspect of child development.

However, finding the right child development research paper topics for your papers can pose a problem. Don’t worry, we’ve got you covered. We have a list of 178 original topics on this page that should work great in 2023.

How Does A Good Research Paper Look Like?

OK, but what does a good research paper look like? Well, to help you out, we’ve put together a simple outline that shows you exactly what your paper should contain:

Introduction Background information on the topic Thesis statement Body #1 (first major subtopic) Statement + a little background information Supporting evidence Body #2 (second major subtopic) Statement + a little background information Supporting evidence Body #3 (third major subtopic) Statement + a little background information Supporting evidence Conclusion Restate the thesis Summarize the key points Call to action Works Cited/Bibliography Appendix

Of course, to be able to write the research paper as fast as possible, you need to find the best possible topic. Stop wasting your time scouring the Internet and choose one of these original topics:

Best Child Development Topics

We will start our list of topics with the best child development topics (or what we consider to work great in 2023). Check out this list of awesome ideas:

• Discuss the Piaget theory on child development
• Research the mechanisms of child development
• Analyze the Toddler stage (1-3 years)
• Research motor skills during child development
• The socio-emotional development of children
• Discuss the 5 stages of development
• Talk about cognitive development
• Research the Preschool stage (3-4 years)
• How does development shape a person’s life?
• Research the role of the environment on development
• Research hands-on experience learning

Easy Child Research Topics

Next on our list we have some of the easiest topics you can find. Our easy child research topics are meant to help you write the paper faster and save time for other activities:

• Discuss the Erik Erikson theory on child development
• Effects of parasites on child development
• A closer look at the Infant stage (3-12 months)
• Effects of race on child development
• The intellectual development of children
• Discuss maternal drug use effects
• Effects of neglect on the development of children
• The 5 stages of child development
• Talk about the Newborn stage
• Analyze the Pre-school stage (4-5 years)

Child Development Project Topics

Are you looking to start a child development project? You certainly need a great idea if you want an A+. Here are some child development project topics you could try:

• Research asynchronous development
• A project on physical growth
• A project on gender role
• A project on language and communication
• Talk about the effects of malnutrition
• Postnatal depression and child development
• Weight growth during child development
• The speed of height growth
• Analyze the mechanisms of change
• A project about individual differences
• Research the development of children with disabilities

Research Topics On Children

If you are looking for interesting research topics on children, you have arrived at the right place. Take a look at these ideas and choose the one you like the most:

• Discuss the Behavioral theory on child development
• An in-depth look at secure attachment
• How do emotions change over time?
• Discuss the transition from dependent to independent
• The effect of family on child development
• The role of movement
• The effect of school on child development
• The importance of playing with other children
• The importance of the surroundings
• The effects of the Covid-19 pandemic
• Psychological changes during development
• Research the effects of classroom environment

Child Development Research Topics

Of course, we have a lot of child development research topics for students of all ages. Here are some of our best, original ideas that should be excellent for 2023:

• Discuss the Vygotsky theory on child development
• The role played by genetics
• Compare and contrast the toddler and the infant
• Compare and contrast the infant and the preschool child
• The importance of a psychologist
• Discuss the role of caregivers
• Compare and contrast the toddler and the newborn
• Effects of positive social interactions
• Research disorganized families
• Compare and contrast the preschool and the school age child
• The negative effects of divorce
• The role of a good early childhood life

Research Paper Topics Children Love

In case you are looking for some research paper topics children love, we have some of the best ideas right here. Check them out and start working on your paper now:

• Latest news in child development
• The importance of a good school
• The importance of eating breakfast
• The role of the mother
• The role of the father
• Teaching sign language to children
• The effects of bullying on children
• Discuss the importance of tangible rewards
• Nurturing good habits
• Sports in the life of a child

Child Development Topics For High School

So what if you’re a high school student? You can write about child development too. We even have some excellent child development topics for high school student right here:

• Discuss ADHD and its effects
• Negative effects of social media on child development
• The role of technology in child development
• Research differently-abled children
• Study the emotional development of children
• An in-depth look at the role of good nutrition
• Research the role of sport in child development
• Research the occurrence of depression
• The struggles of preschool children
• Negative effects of smartphones on child development
• Effects of mass media on school children

Child Development Psychology Topics

Interested in discuss the psychological part of child development? Have a look at our child development psychology topics; you’ll surely find something of interest:

• The different stages of psychological development
• What makes children intelligent?
• Discuss intellectual growth from 3 to 9 years of age
• What makes children put their health at risk?
• Research memory in preschool children
• The problem-solving capabilities of a toddler
• Language learning skills at the age of 3
• Do toddlers have a self-preservation instinct?
• How do toddlers understand the world around them?
• Discuss a school psychology topic
• Research how children think

Interesting Child Development Topics For Papers

Our writers have compiled a list of the most interesting child development topics for papers. All you have to do is choose one of our ideas and start working on your research paper:

• Why is playing so important?
• Talk about the effects of climate change on child development
• How to ensure your child develops properly?
• Discuss the role of social interaction
• Is social media good for child development?
• How do children form their ego?
• The history of child development
• Are some children more intelligent than most adults?
• Research the way children understand life
• Discuss the role of peers on child development

Great Children Research Topics

Are you in search of some great children research topics? You are in luck because we have a long list of such topics right here:

• Research a child’s social development
• Discuss speech development
• Gross motor skills development
• How to monitor child development effectively?
• How important is attention?
• Birth disorders and their negative effects
• Talk about behavioral child development
• The importance of music in child development

Child Development Research Paper Questions

Did you know that the best way to get started on your research paper is to look at some child development research paper questions? Here are some for you:

• How to identify a child genius?
• How does the community affect children?
• Can children overcome trauma?
• How important are birthday celebrations?
• How important is the mother in child development?
• How does the loss of hearing affect children?
• Does the child need to visit a psychologist?
• How does autism influence child development?
• Does Facebook negatively affect a child’s development?
• What is the role of genetics?
• What defines a toddler?
• How important is socialization?
• How much time should a parent spend with his child?
• What is the sociocultural theory?

Current Child Development Topics

Talking about the latest research in child development will surely get you some bonus points. Here are some current child development topics:

• Latest advancements in cognitive child development
• Autistic children development
• Are video games dangerous for child development?
• Severe psychological problems
• Teaching your child a new language
• Research into deviant behavior
• Best games for children to play
• Effects of a poor diet
• The negative effects of a lack of physical exercise
• How does technology influence child development?

Advanced Child Psychology Research Topics

If you want to write about complex topics, we also have a list of advanced child psychology research topics. Choose one of them for free right now:

• The effects of talking on child development
• Discuss the most important development milestones
• The effects of the Covid-19 pandemic lockdowns
• Discuss how television affects child development
• Research the diseases that can hinder child development
• Analyze the connection between a toddler and his parents
• Research child development in single-parent families

Child Development Topics For College

College students will surely appreciate our long list of child development topics for college. Remember, this list is updated periodically so that everyone can get fresh topics:

• The effects of family violence
• Innovative child development techniques
• How much time should you spend with your child?
• Games that stimulate mental growth
• Best ways to solve a behavioral issue
• Negative effects of substance abuse
• Negative effects of divorce

Controversial Child Development Topics

Don’t worry, your teacher will surely appreciate your courage. You shouldn’t be afraid to talk about controversial topics in your research paper. In fact, here are some topics to help you get started:

• Books that children should avoid
• The need for physical punishment
• How important are schools?
• Should children be allowed to play video games?
• The effects of poverty on child development
• Discuss the effects of social insecurity
• Child development in the Indian society

Child Mental Health Essay Topics

Are you interested in talking about the mental health of children? No problem, we have a great list of child mental health essay topics for you:

• Best ways to develop a positive mentality
• An in-depth look at anxiety in toddlers
• Discuss the stages of mental development
• The occurrence of depression in preschool children
• Discuss the cause and effects of ADHD
• Can children suffer from PTSD?
• Research the oppositional defiant disorder

Early Childhood Essay Topics

If you want to cover early childhood in your research paper, you have definitely arrived at the right place. Here are some awesome early childhood essay topics:

• Tourette syndrome in toddlers
• Discuss eating disorders in preschool children
• The effects of social media on young children
• Sports that children should play
• Events that can negatively impact a child’s development
• Ways to ensure maximum mental growth
• Discuss the 5 stages of development and make a comparison between them
• Does music affect the mathematical skills of young children?

Topics Related To Child Psychology

Our experts have created a list of interesting topics related to child psychology that you can use for free. Pick one of these ideas and start writing an A+ paper today:

• Talk about what makes a child intelligent
• Things that negative affect a child’s psychological wellbeing
• Stress in young children in the United States
• Should you child see a psychologist?
• Sports that curb child delinquency
• Discuss the effects of watching excessive television
• The effects of religious orientation on a child’s mental health

ADHD Child Development Essay Topics

Writing about child development of children suffering from the attention deficit hyperactivity disorder is not easy, we know. However, we have some great ADHD Child development essay topics for you:

• How do ADHD children cope with boring situations?
• Controlling the activity levels of ADHD children
• Discuss ways to make ADHD children pay attention
• ADHD’s effects on the ability to focus
• Why do ADHD children have learning disabilities?

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• Open access
• Published: 20 August 2024

Psychosocial interventions for improving the physical health of young people and adults with attention deficit hyperactivity disorder: a scoping review

• John Headley Ward   ORCID: orcid.org/0000-0002-9108-7900 1 , 2 , 3 , 4 ,
• Audrey McBride   ORCID: orcid.org/0009-0003-9000-6667 1 ,
• Anna Price   ORCID: orcid.org/0000-0001-9147-1876 1 &
• Tamsin Newlove Delgado   ORCID: orcid.org/0000-0002-5192-3724 1  

BMC Psychiatry volume  24 , Article number:  569 ( 2024 ) Cite this article

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Young people and adults with ADHD are at risk of a range of physical health problems. There is limited guidance on how to approach health problems in ADHD, and especially around 16-25 year olds who will be transitioning from paediatric to adult care. The aim of this scoping review was to identify psychosocial interventions that target physical health in young people and adults with ADHD.

We constructed searches in MEDLINE, PsycInfo, EMBASE of adolescents, young people and adults. Inclusion criteria were; studies of psychosocial interventions examining a component of physical health, applicable to people aged 16-25, with clinical or research diagnoses of ADHD. Data were extracted using a data extraction tool and tabulated, including study intervention framing/aims, population, intervention, and relevant outcomes (including specific statistics where relevant).

Our search identified 22 unique papers covering, psychosocial interventions targeting at least one of sleep ( n= 7), smoking ( n= 3), substance/alcohol use ( n= 4), physical health/exercise ( n= 6) and general health ( n= 3). Studies examined psychotherapy/behaviour interventions ( n= 12), psychoeducation ( n= 4), digital ( n= 2) and social interventions ( n= 4). There was significant heterogeneity in intervention framing, outcome measures and population.

Further work on the impact of targeted physical health interventions, with explicit reference to a conceptual framework of poor health in ADHD is required. Furthermore, future work standardising reporting of physical health outcomes in ADHD is crucial for the development of an evidence base in this field.

Peer Review reports

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition characterised by combinations of hyperactivity, impulsivity, and inattention, thought to affect 5.6% of 12-18 year olds and 2.58% of adults [ 1 , 2 ]. Whilst traditionally thought of as a disorder of childhood, with a typical onset before the age of 12, it is now understood that symptoms can persist into adulthood and have a significant impact on many aspects of life, including physical health [ 3 , 4 , 5 , 6 ].

In respect to the links in research between ADHD and physical health, firstly there is a wealth of literature on the association between ADHD and higher rates of health risk behaviours, including smoking, alcohol abuse, substance misuse, risk-taking behaviour, self-harm, obesity and sleep disorders [ 6 , 7 , 8 , 9 , 10 , 11 ]. These findings are reproduced in studies using various methods including traits-based approaches, mendelian randomisation, case-control and longitudinal follow-up studies.

Secondly, there is a growing body of evidence demonstrating links between ADHD and non-communicable diseases. A large genetically informed Swedish registry study found that participants with ADHD were at higher risk for 34 out the 35 conditions studied compared to those without ADHD, including nervous system and respiratory disorders [ 12 ]. Other studies have also demonstrated high rates of neurological and respiratory disease, as well as gastrointestinal disorders and cardiovascular disease [ 13 , 14 , 15 ]. Furthermore, Stickley and colleagues [ 15 ] demonstrated that multimorbidity was predictive of whether study participants had ADHD. In respect to mortality, several longitudinal studies have noted increased mortality rates amongst people with ADHD. Whilst these appear to be driven by accidental and unnatural deaths, the cause remains contested [ 6 , 16 , 17 , 18 ].

There have been various attempts to explain the inequalities in physical health outcomes for this population. It has previously been suggested that people with ADHD may be less likely to follow government recommendations on health promotion, even when controlling for socioeconomic status [ 19 ]. This is echoed in work by Cherkasova et al , who reported that the persistence of ADHD symptoms into adulthood mediated poorer functional outcomes [ 6 ]. However, the large sibling analysis study of DuRietz et al highlights the importance of genetic risk factors in the association between ADHD and physical health, supported by their finding that shared genetic factors explained 60-69% of the relationship between ADHD and respiratory, musculoskeletal and metabolic disorders in their sample [ 20 ].

There have been previous studies suggesting that some of the health risks in ADHD may be mitigated by appropriate treatment of ADHD using medication (e.g., meta-analyses demonstrating the efficacy of medication in improving sleep or substance misuse [ 7 , 21 , 22 ]). In addition to medication, psychosocial interventions are likely to be important in the prevention and mitigation of health risks in ADHD, when provided as part of a holistic approach. Importantly, psychosocial interventions can also constitute health promotion and support health autonomy, which may be of particular significance to young adults transitioning to adult care [ 23 , 24 , 25 , 26 , 27 ]. There is a small and heterogenous body of research examining the efficacy of psychosocial interventions in the management of physical health problems associated with ADHD [ 28 , 29 , 30 , 31 , 32 , 33 ]. However, this has not yet been synthesised to identify the nature and extent of existing research or indicate targets for future research and intervention development. This is a significant evidence gap given the poorer physical health of people with ADHD, which adversely affects quality of life and economic, social and health outcomes [ 34 , 35 , 36 , 37 ].

This scoping review aims to identify and describe existing psychosocial interventions for physical health in young people and adults with ADHD, including those in preliminary stages (e.g. feasibility trials).

Given the lack of previous reviews in this field, and the need to provide a broad overview of available evidence, a scoping review was chosen to identify psychosocial interventions addressing physical health in ADHD. Scoping reviews are suitable for identifying research gaps, summarising research findings, clarifying concepts, and making recommendations for future research [ 38 ]. This scoping review aimed to identify relevant literature using an inclusive approach incorporating different methodologies and reflecting varying levels of quality [ 39 ].

The review followed a five-stage process as described by Arksey and O'Malley: identifying the question, identifying relevant studies, study selection, charting the data and collating, summarising and reporting the results [ 40 , 41 ]. We found no previous scoping reviews or systematic reviews examining this topic. We have reported our scoping review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review Extension checklist (see supplementary materials) [ 42 ]. We did not pre-register this review protocol.

Eligibility criteria

Studies were eligible for inclusion in the review if they met four key eligibility criteria: a population aged 16 years or older (or including substantial representation of this group), diagnosed with ADHD (either clinically diagnosed, self-reported, or using a standardised diagnostic measure) (population and context), the introduction of a form of structured psychosocial intervention within an experimental trial (concept) and the measurement of a physical health outcome (outcome).

In respect to defining the population of interest, we sought interventions that would be relevant to young people and adults, of a transition care age group (16-25 year olds). This age bracket is important for two reasons. Firstly, it is well-understood that ADHD care begins to decline for older adolescents, as medication adherence and service access decline [ 25 , 26 ]. Secondly, the transition to adulthood is when adolescents begin to take responsibility for their own health and health behaviour, and therefore support around independent health management would be timely [ 23 , 24 , 27 ].

To meet the scoping review’s aim of identifying all interventions relevant to the population, we included studies of under 16s, and some studies of adults over 25 years old. This was the case where the proposed intervention had methods or findings that were clearly applicable to 16–25-year-olds. ‘Applicable’ in this context was defined as interventions that could be utilised in our population of interest without need for modification of the intervention itself. Given that this was a scoping review, we judged this was an appropriately inclusive approach to exploring a limited literature, with similar expanded definitions of age categories having been used in previous scoping reviews [ 43 , 44 , 45 ]. We did however exclude school-based interventions, (e.g., those which use a school or classroom-based approach in childhood) [ 46 ]. This was because our team considered that interventions set within classroom environments would not be replicable in young adults. Where inclusion criteria were borderline, decisions were made on a case-by-case basis and discussed by at least two reviewers (TND and JW).

For the purposes of this review, psychosocial interventions were defined as structured interventions that adopt a psychological, educational, or social framework. This definition was adapted from Ruddy and House, adapting the definition to include digital health interventions, which have taken prominence since the publication of their definition in 2005 [ 47 , 48 , 49 ]. In this review, we included search terms pertaining to psychotherapeutic interventions, behavioural interventions, digital interventions, peer/support groups, exercise-based interventions, and psychoeducational interventions.

Study outcomes were checked during the screening process to identify physical health outcomes. We defined physical health broadly as a chronic physical health problem and/or a current behaviour that confers a long-term physical health risk (e.g., unprotected sex, smoking). This definition was formed in collaboration with the Managing Young People with ADHD in Primary Care (MAP) study academic team and research advisory group (RAG) which was composed of people with lived experience [ 50 ]. Physical health outcomes included scales (e.g., sleep indices, health-related quality of life), objective measures (e.g., reductions in alcohol consumption, abstinence) and subjective measures (e.g., sleep diaries). Studies were excluded if there was no clear physical health outcome recorded in either the published paper or its supplementary materials. We deliberately did not pre-define specific physical health concerns in our search. This was because, in conjunction with our MAP study advisory team, we felt this would be a more appropriate approach for an initial exploration aimed at capturing the breadth of health problems being addressed. In pre-defining health problems, we considered there would be a risk of excluding studies which incidentally notes physical health outcomes.

Studies from the grey literature were excluded, as well as studies not written in the English language, due to resource limitations. We also excluded non peer-reviewed scientific literature (e.g. dissertations, preprints, conference proceedings). We did not exclude studies where participants received a biological therapy (e.g. medication, bright light therapy), if they also received a psychosocial intervention. This approach enabled a broad spread of relevant included studies and met the review’s objective of identifying feasible interventions.

Search strategy

The search strategy was developed with information specialists at the at the University of Exeter. Searches were performed using MEDLINE (1946 onwards), Embase (1974 onwards ) and PsycInfo (1803 onwards ), via the Ovid © platform.

Searching took place in two phases, to ensure adequate inclusion of young people/youths and adults (Fig. 1 ). In the first phase, we used our young people/youth search terms and our adult terms (search dates 7 th October 2022 and 24 th November 2022 respectively). The process of search design through the completion of title and abstract screening was from September 2022 to December 2022, with full-text inclusions from this search decided by January 2023.

Flow diagram of database searches, title/abstract screening and full text screening

In order to ensure that we included publications relating to applicable interventions that were tested in a younger population (i.e. 13-17 year olds), a second phase included a search using adolescent search terms, conducted in February 2024, with title/abstract and full text-screening screening completed in March 2024. This search included literature published up until February 2024. Full details of all searches can be seen in supplementary materials.

ADHD search terms were adapted from the search terms used by the National Institute for Care and Health Excellence (NICE) in their development of ADHD guidance [ 51 ]. Search terms for psychosocial interventions were adapted from the search terms used by NICE in the development of their guidance for lower back pain and diabetes [ 52 , 53 ]. These were adapted as appropriate for our search and are available in supplementary materials.

Study selection

The study selection process is highlighted in Figure 1 . The first set of searches (young people/adults, October-November 2022) yielded 5258 results, and the second (adolescents, February 2024) 4293.

These studies were then screened by title and abstract independently by two reviewers (JW, TND), against inclusion criteria, with disagreements resolved by discussion. Where disagreements were not resolved, this was taken to the wider study team and MAP study principal investigator (PI) (AP). Citation chasing was also performed by examining references from relevant review and protocol studies to identify any further studies not found in our search.

This left 61 records for full-text screening. These were again double-screened (JW, TND), with disagreements resolved by discussion, and where necessary the wider study team, and principal investigator (AP), leaving 22 articles which were included at full-text screening. Reasons for full-text exclusions are given in Figure 1 .

Data extraction and charting

Studies were collated using a data extraction form and shared spreadsheet in which the data could be recorded. This data extraction tool was piloted on five papers initially, reviewed and then used for all papers. These were single entered by researchers (JW, AM), with all entries were re-reviewed after first entry (JW). The data extraction tool can be found in supplementary materials.

The data extraction process used narrative synthesis to collate information on what the intervention was targeting (and rationale), what outcomes were measured and how these were measured. This involved extracting study details (i.e., title, author), study design (comparator, methodology), population characteristics (age, gender, location of study), intervention framing of study (i.e. rationale for intervention chosen), ADHD definition (e.g., meeting DSM-V criteria, clinically diagnosed ADHD), relevant additional inclusion/exclusion criteria, primary and secondary outcomes of the studies and measures used, physical health findings, attendance reporting and ADHD symptom findings. Where studies had noted qualitative feedback on the interventions used, this was also collated and charted under outcomes.

Data were then charted in tabular form, by physical health problem addressed, with the extracted details on the studies provided alongside this.

Twenty-two studies met our inclusion criteria (Table 1 ). Physical health outcomes targeted or reported included sleep (seven studies), smoking (three studies), substance misuse (four studies), physical activity and/or weight (six studies) and more general/broad physical health outcomes (three studies). It should be noted that one study (Bjork et al .) covered two health outcomes (smoking, physical activity) [ 54 ]. Studies covered an overall age range of 11-65. Of these, eleven studies examined adolescents, ten studies examined adults (although four did not provide a precise age range), and one study examined both (14–30-year-olds) [ 55 ]. Only one included study had participants exclusively between 16-25, but this was a college-based study [ 56 ].

In respect to ADHD concept, 14/22 studies were based on clinical diagnosis, whilst 6/22 were criteria based, 1/22 used self-reported ADHD and 1/22 used ‘documented’ ADHD (Table 1 ). Where studies reported gender ( n= 16), 10 studies were at least 50% female, ranging from a 32% to 83% male sample. 14/22 studies included a physical health outcome as a primary outcome or target, whilst 5/22 studies included physical health as a secondary outcome [ 55 , 56 , 60 , 61 , 74 , 75 ]. 12/22 of the studies were of a psychotherapeutic or behavioural intervention, 4/22 of psychoeducation, 4/22 social/exercise interventions and 2/22 digital interventions. Most of the studies were conducted in the USA (8/22), followed by Sweden (5/22), the Netherlands (2/22) and Germany (2/22), with the others located in Brazil, Norway, Belgium, Denmark and China.

In respect to methodology, 13/22 studies were randomised controlled trials (RCTs) [ 56 , 63 , 66 , 67 , 68 , 70 , 75 , 76 , 77 ], 6/22 studies were single group (before and after) comparisons [ 54 , 57 , 59 , 60 , 69 , 73 ], one study was secondary analysis of RCT data [ 58 ], one study compared a single-group pre/post intervention with a previous study data [ 74 ], and finally one study compared two groups before and after comparison (not RCT) [ 64 ]. Apart from one study which was unfunded [ 73 ], and one study which did not clarify its funding [ 54 ], 20/22 studies were funded from non-commercial sources.

Sleep was examined as a health outcome in seven included studies, as described below in Table 2 [ 55 , 57 , 58 , 59 , 60 , 61 , 77 ]. All used different interventions, which can be broadly divided into psychoeducational interventions and psychotherapeutic interventions (e.g., adapted cognitive or dialectical behavioural therapy). One study examined primarily bright light therapy, however used psychoeducation around sleep in their methodology for both active arms and the placebo arm (hence its inclusion). Only one study included people with diagnosed sleep problems and ADHD, with the others including either a general ADHD population or those with self-reported sleep problems. Four of the studies included are completed or ongoing RCTs, with the rest being pilot/feasibility studies or single group intervention studies. Included studies had small sample sizes (three had fewer than 20 participants, only one had a sample size greater than 100) and covered a wide age range (13-63). Three studies suggested a rationale for their intervention within ADHD in relation to health needs; ADHD symptoms/executive dysfunction impacting on habits and sleep hygiene as the mechanism of sleep problems in ADHD [ 58 , 59 , 62 ] and delayed circadian rhythm/preference [ 58 , 59 ]. Whilst Becker et al referenced problems of adolescence in sleep, they did not explain the rationale within ADHD [ 57 ]. Van Andel et al (RCT (melatonin versus placebo versus melatonin and bright light therapy, where all arms received psychoeducation) did not find improvements in sleep for any group [ 58 ]. Meyer et al (RCT) also did not find sustained improvements in sleep for either their behavioural or control (psychoeducation group) [ 55 ]. However, the single group intervention and pilot studies did find evidence supporting behavioural and psychosocial interventions, including pilot feasibility data from Keuppens et al RCT [ 77 ]. Results also demonstrated tolerability and feasibility of these sleep interventions in ADHD; all completed studies noted good attendance at and compliance with interventions, whilst Becker et al. , Jernelov et al . and Keuppens et al. noted participants’ satisfaction with interventions. The subjective positive feedback received in Becker et al. included increased responsibility for health, working with a therapist and increased knowledge [ 57 ]. In Jernelov et al ., feedback received was the use of routines and structure [ 59 ]. For Keuppens et al. , thematic analysis generated themes for adolescents around having more control and independence around sleep, and that both parents and adolescents had better understanding of the impact of ADHD on sleep [ 77 ].

Smoking was examined as a health outcome in three studies, as presented in Table 3 [ 54 , 63 , 64 ]. These studies had an average sample size of 45 and covered both adolescents and adults. One of the studies was a randomised controlled trial (RCT), whilst the other two were a single-group intervention study and an ADHD vs non-ADHD single intervention study, neither with control groups. Two of the studies used psychoeducation, including components about smoking, whilst one of the studies used monetary incentives to encourage participants to stop smoking. In respect to mechanisms, two of the three studies suggested a rationale for their choice of intervention; targeting executive dysfunction in ADHD that may perpetuate smoking [ 54 , 64 ] and mental health difficulties in ADHD precipitating poor health behaviour [ 54 ]. The results were variable. The two studies examining tobacco use (Kollins et al ., Bjork et al .—non-randomised group trials) found no interventions with sustained effects, reporting that participants largely went back to smoking (irrespective of ADHD). Corona et al.’s study (also an RCT) found that the attitudes of participants towards substance misuse changed significantly following specific work around tobacco, however they did not examine tobacco use directly. Bjork et al and Corona et al both noted that participants generally adhered well to the intervention [ 54 , 63 ]. In respect to specific positives of interventions, Björk et al. cite peer support dynamics in their group [ 54 ].

Substance misuse

Outcomes related to alcohol and substance misuse were examined in four studies, as seen in Table 4 [ 65 , 66 , 67 , 68 ]. These all had relatively larger sample sizes (range=70-303) and were RCTs. They all included participants who had diagnosable substance misuse disorders, rather than subclinical problematic substance use, (in contrast to the studies of sleep). Two of the studies examined cognitive behavioural therapy (CBT) paradigms, whilst one study evaluated at motivational interviewing (MI) and behavioural action and one used both CBT/MI. Two studies identified a rationale for their choice of intervention; untreated ADHD symptoms being associated with poorer outcomes in substance use disorder [ 67 , 68 ], and the challenges of people with ADHD within a college environment putting them at greater risk for long-term substance misuse [ 66 ]. All four studies (RCTs) reported significant improvements in measured outcomes with a psychotherapeutic intervention, including Riggs et al. and Thurstone et al. which found that behavioural therapy and medication had comparable effects in the treatment of substance use disorder in patients with ADHD [ 67 , 68 ].

Physical activity/weight

Studies reporting physical activity or weight outcomes were much more heterogenous in their design, including two RCT protocols, two completed RCTs and two single group interventions (Table 5 ). Studies in this category had generally small sample sizes (n<50), except Lindvall et al ( N= 120) [ 71 ] and comprised a younger adult demographic (11-30). Only two studies provided a rationale for intervention explicitly highlighting health in ADHD (both referencing poor health behaviour in ADHD) [ 54 , 71 ]. All involved promoting physical activity, through structured exercise classes, wearable technology/social media and psychoeducation respectively. Furthermore, Schoenfelder et al. report qualitative feedback that the intervention increased awareness of activity levels and ADHD symptoms [ 69 ]. Both RCTs (Silva et al, Converse et al [ 56 , 72 ]) reported improved physical functioning (Converse et al using a questionnaire, Silva et al using objective biometrics), as did both single group intervention studies (Schoenfelder et al finding an increase in step count, Bjork et al in weekly physical activity [ 54 , 69 ]).

Unspecified physical health outcomes

Three studies examined unspecified physical health outcomes related to quality of life and did not fit well into other categories (Table 6 ) [ 73 , 74 , 75 ]. Enggaard et al. reported a study of adolescents with a comorbid physical health disorder, examining guided self-determination as a way of improving their engagement in physical healthcare, given the association of ADHD with physical comorbidity. They found that guided self-determination was effective in improving patients’ self-confidence in managing their conditions, and that adolescents were positively engaged in creating the self-management strategies. The second study examined effects of medication versus cognitive behavioural therapy in 124 young adults on core ADHD symptoms and secondarily recorded improvements in physical health as part of questions on the World Health Organisation (WHO) quality of life scale [ 78 ]. This study [ 74 ] did not identify a rationale for their intervention’s impact physical health. Thirdly, Geissler et al developed a modular treatment programme for adolescents with continual ADHD-related impairment (under routine care). Their rationale was the breadth of functional impairment faced by adolescents with ADHD, and the lack of related interventions. Their developed RCT protocol includes a health-related quality of life questionnaire as a secondary outcome, and their intervention includes a module on substance use [ 75 ].

This scoping review aimed to identify psychosocial interventions that have been designed for physical health problems in ADHD, and which physical health problems they target. We found 22 studies of interventions which measured at least one physical health outcome, with 16 specifically targeting physical health outcomes. In the other studies, measures of physical health (including sleep quality or health-related quality of life measures) were included as secondary outcomes of interventions primarily targeting reduction of core ADHD symptoms [ 55 , 56 , 60 , 61 , 74 , 75 ]. Included studies were grouped under five categories, dependent on the outcomes explored. These were sleep, smoking, substance misuse, physical activity/weight, and general health outcomes, utilising psychoeducational, behavioural and social paradigms (Table 1 ).

The main finding from this scoping review is a relative paucity of research into interventions targeting physical health outcomes in ADHD, and furthermore the lack of larger programmes of research aiming to address the health problems identified. Generally, the included studies lacked detail on the framing and theoretical basis both of individual health problems (who is affected, and how that health problem is quantified) as well as of health problems in ADHD in general (the 'mechanism' of ill health targeted by such interventions). Fortunately, there is some similarity amongst the identified literature explored in respect to the psychosocial interventions used and identified positive aspects of interventions, which may form a basis for the development of a more coherent evidence base in this field.

Framing of health problems

There is substantial heterogeneity in this literature in respect to how health problems were defined and measured, with variable inclusion criteria and outcome measures between studies. For example, when exploring sleep, some studies examined those with formal sleep diagnoses [ 58 ], whilst others specifically excluded those with diagnosed sleep problems [ 59 , 62 ]. In relation to outcome measures, smoking was conceptualised in a different way by each of the studies included (attitudes to tobacco, carbon monoxide levels and self-reported reductions). Some studies used standardised quality of life measures, such as the WHOQL-BREF, SF-36, and KIDSCREEN-10 [ 56 , 74 , 75 ]. However, quality of life measures are of limited utility in assessing physical health outcomes, often being too broad and multi-factorial. We also note a recent scoping review finding that the SF-36 is frequently erroneously reported as a global measure of quality of life, which although Converse and colleagues did not do, highlights a wider problem with the misapplication of quality-of-life measures [ 79 ]. The heterogeneity of included studies’ outcome measures highlights the need for consensus in respect to measures used in assessing the physical health outcomes of populations with ADHD. It was interesting that three of the six studies that did not explicitly target a health problem used sleep outcome measures in behavioural interventions [ 55 , 60 , 61 ], which may highlight the importance of sleep to young people and families, and the impact poor sleep has on symptoms and functioning [ 80 , 81 ].

Such extensive variability in inclusion criteria and outcome measurements limits both the clinical and academic applicability of studies’ findings. This variability is likely to result from the absence of a common framework that mechanistically relates ADHD and physical health outcomes.

Whilst there was some commonality in intervention modalities (e.g., behavioural interventions, educational interventions), authors tended not to explain clearly which mechanism within ADHD their health intervention was targeting, beyond a select few [ 54 , 57 , 58 , 59 , 62 , 64 , 66 , 71 , 73 ]. Challenges surrounding poor conceptual framework of mechanisms of ADHD in relation to health are alluded to in the discussions of some of the included studies [ 54 , 58 , 59 , 64 , 66 , 67 , 73 ]. As mentioned in the introduction, the ‘causal pathway’ of increased health risk in ADHD is likely to be complex and multifactorial, however a sound understanding and explicit logic model is an important basis for the development of preventative interventions in this population. Findings from this scoping review suggest that that clearer framing of the problem is required to properly develop interventions, through better definition of health problems with inputs from existing research and stakeholder perspectives (which may explain the currently disjointed view of this field) [ 82 ].

Positive aspects of interventions

Psychoeducation was common amongst health interventions studied, with 4/22 solely examining a psychoeducational intervention, and Meyer et al comparing a behavioural intervention with psychoeducation as control [ 55 ]. These studies tended to recruit younger participants who were ‘at risk of’ particular health problems, with only Bjork et al using psychoeducation in an adult context. This raises questions about where future research work should focus, primary or secondary prevention in young people and adults with ADHD.

‘Self-efficacy’ or independence over one’s health was also a concept referenced explicitly in the qualitative feedback from participants included in several of the studies we reviewed [ 57 , 73 , 77 ]. Furthermore, all the interventions in included studies all required commitment to interventions and required people to actively engage in their own care, the importance of which has been studied previously in patients with chronic conditions [ 83 , 84 , 85 ]. Self-efficacy is widely cited as being important in ADHD management [ 86 , 87 ]. This is explicitly highlighted by Enggaard et al. , who demonstrated that their guided self-determination intervention promoted efficacy and strategy formation amongst patients with ADHD [ 73 ].

Regular and consistent interventions (regular sessions, commitment to a regimen), were explicitly highlighted in the qualitative participant feedback on several interventions [ 59 , 69 ]. This is particularly pertinent in ADHD, where difficulty with day-to-day structure and organisation is something that people highlight as a contributor to health and social outcome inequalities [ 88 , 89 , 90 ].

Peer dynamics were also referenced by several papers [ 54 , 56 ]. Bjork et al. reported that participants found the peer support dynamic of such interventions useful, whilst Converse et al. reported that participants from an earlier survey used in the development of their intervention would have preferred a mixed ADHD/non-ADHD group [ 91 ]. From a brief review of the literature, the perspectives on peer support in adult ADHD have not yet been formally studied but could be looked at in future work. It should be noted that, in discussions about ADHD in online spaces, community and identity appear to be important themes in living with ADHD [ 87 , 92 ].

If the literature in this field were more coherent, it would make it easier to explore facets of interventions in this field more rigorously, using methods such as intervention component analysis. This would be especially interesting given the findings of Meyer et al, which suggest comparable effects between psychoeducation and behavioural intervention [ 55 ].

Strengths and limitations

This study addresses a novel research question in the literature and our search strategy identified papers in line with research aims. By not defining physical health in our search strategy, we were able to identify a broad range of interventions, targeting for example sleep, smoking, alcohol/substance misuse, physical activity, weight, and physical comorbidity.

Limitations of our scoping review include challenges around defining population age range. Of the 22 studies included, only one study explicitly fell within the 16-25 age range [ 56 ]. Whilst it may have been preferable to strictly apply the lower age limit of 16 years, doing so would have risked losing studies with applicability to our 16-25 age group (e.g., Schoenfelder and colleague’s study of digital health, many of the sleep behavioural interventions) [ 57 , 61 , 69 ]. The same would apply to the upper age limit, where studies such as Björk et al would be excluded if a strict age basis was applied (despite this study having clear relevance to our question) [ 54 ]. Therefore, we adopted a pragmatic approach, informed by consultation with MAP study colleagues and our RAG. We accept that the interventions would likely have different effects than those reported by the studies, if they were to be repeated in a strictly 16-25 age group. This would be an important subject of future work, supported by framework development.

By defining ‘types’ of interventions we were interested in for our search (psychotherapeutic, behavioural, technological, support groups, exercise-based, psychoeducational) we may have inadvertently precluded the inclusion of other interventions in the field. However, to deliver the review with the resources available, and following consultation with our RAG, it was decided to prioritise an open approach to defining physical health problems, which came at the cost of being more restrictive in terms of types of intervention reviewed. As this research area matures, and concepts related to ADHD and physical health become more clearly defined, it will become easier to conduct evidence syntheses of literature on this topic.

Furthermore, it was notable that there were limited interventions surrounding established chronic physical disorders targeted at adults with ADHD, given the known associations of ADHD with chronic health problems [ 12 , 14 , 93 ]. However, this is likely because our search filters examining psychosocial interventions would not have been inclusive of tailored medical interventions (e.g. if a study were examining supporting people with ADHD and diabetes in their medication compliance). A focussed review of chronic disease management in ADHD in adults would be useful in exploring this important area.

This scoping review set out to identify existing psychosocial interventions for physical health in ADHD, with a focus on interventions applicable to a transition care age range (16-25 year olds). Findings demonstrate that whilst such interventions have been developed and reported, the small evidence base surrounding them limits their current application. Future work in this field needs to focus on the development of a conceptual framework for the origins of the physical health challenges and linked health inequalities we see in ADHD. Alongside this, more research is needed into creating standardising how health outcomes are measured and reported in ADHD research in this field, such that evidence can be better synthesised and ultimately realised into clinical applications.

Availability of data and materials

The datasets generated and/or analysed during the current study are available via the MEDLINE ( https://www.nlm.nih.gov/medline/medline_overview.html ), APA PsycInfo ( https://www.apa.org/pubs/databases/psycinfo ) and EMBASE ( https://www.embase.com/ ) databases.

Abbreviations

Attention deficit hyperactivity disorder

Cognitive Behavioural Therapy

Diagnostic and Statistical Manual of Mental Disorders Fifth Edition

Kiddie Schedule for Affective Disorders and Schizophrenia Present and Lifetime

Mapping ADHD services in Primary Care Study

National Institute of Health and Care Excellence

Research Advisory Group

Randomised Control Trial

36-item Short Form Survey

World Health Organisation

World Health Organisation Quality of Life (Brief) Scale

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Acknowledgements

we would like to express our thanks to our public patient involvement group and research advisory group, who facilitated our approach to this important research topic. We would also like to thank Reviewer 2, whose detailed and thoughtful comments have greatly strengthened the content and form of this manuscript.

AP is funded by a National Institute for Health and Care Research (NIHR) Three Research Schools’ Mental Health Research Fellowship (located within the Exeter NIHR School for Primary Care Research (SPCR); Grant Reference Number MHF008). Tamsin Newlove-Delgado was funded by a NIHR Advanced Fellowship (NIHR300056) whilst undertaking this work. The views expressed in this publication are those of the authors and not necessarily those of the NIHR, NHS or the UK Department of Health and Social Care.

JW is supported by the NIHR Oxford Health Biomedical Research Centre (BRC)

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JW was responsible for hypothesis generation, design of literature search, title/abstract screening, data extraction, analysis and manuscript preparation. AM was responsible for data extraction and manuscript preparation. AP was responsible for design of literature search and manuscript preparation, as well as project oversight. TND was responsible for title/abstract screening and manuscript preparation, as well as project oversight.

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Ward, J.H., McBride, A., Price, A. et al. Psychosocial interventions for improving the physical health of young people and adults with attention deficit hyperactivity disorder: a scoping review. BMC Psychiatry 24 , 569 (2024). https://doi.org/10.1186/s12888-024-06009-2

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Received : 12 September 2023

Accepted : 08 August 2024

Published : 20 August 2024

DOI : https://doi.org/10.1186/s12888-024-06009-2

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