Lifespan Development. Tara L. Kuther

logical reasoning. Measuring intelligence in infancy is challenging because, as noted earlier, infants cannot answer questions. Instead, researchers who study infant intelligence rely on an assortment of nonverbal tasks—the same kinds of methods that are used to study cognitive development. There are two general approaches to studying intelligence in infancy. As discussed next, the testing approach emphasizes standardized tests that compare infants with age-based norms. A second approach, the information processing approach, examines specific processing skills.

      Testing Approach to Intelligence

      At 3 months of age, Baby Lourdes can lift and support her upper body with her arms when on her stomach. She grabs and shakes toys with her hands and enjoys playing with other people. Lourdes’s pediatrician tells her parents that her development is right on track for babies her age and that she shows typical levels of infant intelligence. Standardized tests permit the pediatrician to determine Lourdes’s development relative to other infants her age.

      The most often used standardized measure of infant intelligence is the Bayley Scales of Infant Development III (BSID-III), commonly called “Bayley-III” (see Figure 5.7). This test is appropriate for infants from 1 month through 42 months of age (Bayley, 1969, 2005). The Bayley-III consists of five scales: three consisting of infant responses and two of parent responses. The Motor Scale measures gross and fine motor skills, such as grasping objects, drinking from a cup, sitting, and climbing stairs. The Cognitive Scale includes items such as attending to a stimulus or searching for a hidden toy. The Language Scale examines comprehension and production of language, such as following directions and naming objects. The Social-Emotional Scale is derived from parental reports regarding behavior such as the infant’s responsiveness and play activity. Finally, the Adaptive Behavior Scale is based on parental reports of the infant’s ability to adapt in everyday situations, including the infant’s ability to communicate, regulate his or her emotions, and display certain behavior.

      The Bayley-III provides a comprehensive profile of an infant’s current functioning, but the performance of infants often varies considerably from one testing session to another (Bornstein, Slater, Brown, Roberts, & Barrett, 1997). Scores vary with infants’ states of arousal and motivation. This suggests that pediatricians and parents must exert great care in interpreting scores—particularly poor scores—because an infant’s performance may be influenced by factors other than developmental functioning. Alternatively, some researchers have argued that perhaps the variability in Bayley-III scores from one occasion to another suggests that intelligence itself is variable in infancy (Bornstein et al., 1997). Regardless, the low test–retest reliability (see Chapter 1) means that infants who perform poorly on the Bayley-III should be tested more than once.

      Although Bayley-III scores offer a comprehensive profile of an infant’s abilities, scores do not predict performance on intelligence tests in childhood (dos Santos, de Kieviet, Königs, van Elburg, & Oosterlaan, 2013; Rose & Feldman, 1995). Even Nancy Bayley, who invented the Bayley Scales, noted in a longitudinal study (1949) that infant performance was not related to intelligence scores at age 18. Why is infant intelligence relatively unrelated to later intelligence? Consider what is measured by infant tests: perception and motor skills, responsiveness, and language skills. The abilities to grasp an object, crawl up stairs, or search for a hidden toy—items that appear on the Bayley-III—are not measured by childhood intelligence tests. Instead, intelligence tests administered in childhood examine more complex and abstract abilities such as verbal reasoning, verbal comprehension, and problem solving.

      Figure 5.7 Bayley-III Scales (BSID-III)

      Infant assessment tests, such as the BSID-III, examine cognitive, language, social-emotional, and motor abilities, such as infants’ skill in manipulating objects.

      Source: Cliff Moore / Science Source

      If the Bayley-III does not predict later intelligence, why administer it? Infants whose performance is poor relative to age norms may suffer from serious developmental problems that can be addressed. The intellectual abilities measured by the Bayley-III are critical indicators of neurological health and are useful for charting developmental paths, diagnosing neurological disorders, and detecting intellectual disabilities in infants and toddlers. Thus, the Bayley-III is primarily used as a screening tool to identify infants who can benefit from medical and developmental intervention. As discussed in the accompanying Brain and Biological Influences on Development feature, contextual conditions, especially exposure to poverty, can place some infants and children at risk for poor cognitive development and lower IQ.

      Intelligence as Information Processing

      The challenge in determining whether intelligence in infancy predicts performance in childhood and beyond rests in identifying measures that evaluate cognitive functioning from infancy through childhood. Information processing abilities, such as those related to attention, working memory, and processing speed, underlie performance in all cognitive tasks, including intelligence tests, and are therefore important indicators of intellectual ability that are evident at birth and persist for a lifetime (Baddeley, 2016; Müller & Kerns, 2015; Ristic & Enns, 2015).

      Individuals who process information more efficiently are thought to acquire knowledge more quickly. This is true for infants as well as for older children and adults. Indeed, information processing capacities in infancy, such as attention, memory, and processing speed, have been shown to predict cognitive ability and intelligence through late adolescence.

      Brain and Biological Influences on Development

      Poverty and Development

      Poverty has a detrimental effect on children’s development and is associated with deficits in memory and learning, cognitive control, and emotional processing. Chronic poverty is especially damaging because the neurological and cognitive deficits accumulate over childhood.

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      Forty-five percent of U.S. children under 3 years of age (including two thirds of Black, Hispanic, and Native American children) live in low-income families (income less than $48,000 per year for a family of four), and 23% live in poor families (income less than $24,000) (Koball & Jiang, 2018) (see Table 5.8). In 2013, the American Academy of Pediatrics added child poverty to its Agenda for Children in recognition of poverty’s broad and enduring effects on child health and development (American Academy of Pediatrics, 2017). Infants and children from poor families experience higher rates of malnutrition, growth stunting, and susceptibility to illness than do their peers (Yoshikawa, Aber, & Beardslee, 2012).

      Exposure to chronic long-term poverty has negative effects on brain growth and is associated with lower volumes in parts of the brain associated with memory and learning, cognitive control, and emotional processing (Johnson, Riis, & Noble, 2016; Ursache & Noble, 2016). For example, a longitudinal study of 77 children from birth to age 4 revealed a link between poverty and lower gray matter volume especially in the frontal and parietal regions associated with executive function (Hanson et al., 2013). In another study, 5-week-old infants in low socioeconomic status (SES) homes tended to have smaller brain volumes than other infants, suggesting that poverty may influence biological and cognitive development during the first few weeks of life or earlier (Betancourt et al., 2016).

      The effects of socioeconomic status on development vary. SES is more closely related with brain structure and cognition in children from poor homes than high SES homes (Hair, Hanson, Wolfe, Pollak, & Knight, 2015; Noble et al., 2015). That is, the detrimental effect of low SES contexts is a greater