Network structure reveals clusters of associations between childhood adversities and development outcomes

Abstract

Exposure to childhood adversity is common, with more than half of children in the United States experiencing at least one form of adversity by the time they reach adulthood (Green et al., 2010; McLaughlin et al., 2012). It has been clearly demonstrated that these experiences are strongly associated with risk for negative outcomes in childhood, adolescence, adulthood, and late adulthood (Cicchetti & Toth, 1995; Green et al., 2010; McLaughlin et al., 2010). The prevailing approach used to examine the consequences of adversity exposure for health is a cumulative risk (CR) model (Evans, Li, & Whipple, 2013; Felitti et al., 1998). In this model the number of exposures to adversity is summed to create a risk score which is used to predict outcomes such as cognitive abilities, emotion regulation, or psychopathology (Evans et al., 2013). The CR model has been useful in highlighting the strong links between adversity exposure and health outcomes and has pushed the field toward reducing exposure to adversity and providing intervention to the most vulnerable. However, the CR model gives little guidance with regards to the mechanisms through

The Value of Dimensional Models of Early Experience: Thinking Clearly About Concepts and Categories

“…Indeed, a number of recent empirical studies designed specifically to evaluate propositions of dimensional models yield evidence consistent with these ideas. This includes work supporting the predicted distinctions between threat and deprivation in their associations with a range of developmental outcomes, such as amygdala reactivity to threat, aversive learning, cognitive control, and even pubertal timing (Goetschius et al, 2020;Hein et al, 2020;Lambert, King, Monahan, & McLaughlin, 2017;Machlin, Miller, Snyder, McLaughlin, & Sheridan, 2019;Miller, Machlin, McLaughlin, & Sheridan, 2020;Miller et al, 2018;Peckins et al, 2020;Rosen, Meltzoff, Sheridan, & McLaughlin, 2019;Sheridan, Peverill, & McLaughlin, 2017;Sheridan et al, 2020;Sumner, Colich, Uddin, Armstrong, & McLaughlin, 2019;Sun, Fang, Wan, Su, & Tao, 2020;Wolf & Suntheimer, 2019). Perhaps the strongest evidence comes from systematic reviews and meta-analyses that document clearly divergent associations of threat and deprivation with neural structure and function (McLaughlin, Weissman, & Bitran, 2019) and measures of biological aging, including pubertal timing and cellular aging (Colich, Rosen, Williams, & McLaughlin, 2020).…”

Direct and indirect links between children’s socio-economic status and education: Pathways via mental health, attitude, and cognition

“…Relative to their peers, children from disadvantaged backgrounds demonstrate lower performance on tests of attention (D'Angiulli et al, 2008;Kishiyama et al, 2009;Lipina et al, 2013;Mezzacappa, 2004;Neville et al, 2013;Stevens et al, 2009;Weatherholt et al, 2006), shortterm memory (Farah et al, 2006;Kishiyama et al, 2009;Lipina et al, 2013;Noble et al, 2007;Sarsour et al, 2011), long-term memory (Farah et al, 2006;Noble et al, 2007), executive function (Farah et al, 2006;Kishiyama et al, 2009;Lipina et al, 2005Lipina et al, , 2013Noble et al, 2005Noble et al, , 2007, inhibition (Farah et al, 2006;Lipina et al, 2013;Noble et al, 2005;Sarsour et al, 2011;Sheridan et al, 2020), phonological awareness (Noble et al, 2005(Noble et al, , 2006(Noble et al, , 2007Whitehurst, 1997), reading-DALMAIJER ET AL. SOCIO-ECONOMIC STATUS AND CHILD DEVELOPMENT related factors (Dolean et al, 2019;Noble et al, 2006;Sheridan et al, 2020), and general intelligence (Brito & Noble, 2014;Brooks-Gunn & Duncan, 1997;Gottfried et al, 2003;Hanscombe et al, 2012; J. R. . Indeed, Sheridan and colleagues use a network approach to demonstrate that deprivation is tightly connected with cognitive performance, more so than with emotional reactivity measures (Sheridan et al, 2020).…”

“…SOCIO-ECONOMIC STATUS AND CHILD DEVELOPMENT related factors (Dolean et al, 2019;Noble et al, 2006;Sheridan et al, 2020), and general intelligence (Brito & Noble, 2014;Brooks-Gunn & Duncan, 1997;Gottfried et al, 2003;Hanscombe et al, 2012; J. R. . Indeed, Sheridan and colleagues use a network approach to demonstrate that deprivation is tightly connected with cognitive performance, more so than with emotional reactivity measures (Sheridan et al, 2020). Importantly, although cognitive ability is partly hereditary, it is also impacted directly by environmental factors such as SES (Capron & Duyme, 1989;Hamadani et al, 2014;Hanscombe et al, 2012;Marcus Jenkins et al, 2013;Stumm et al, 2019;Turkheimer et al, 2003).…”

How Early Life Adversity Transforms the Learning Brain

“…Building on decades of research on animals, together with their own studies of human infants, children and adolescents, McLaughlin (2016, 2020); Sheridan, Shi, Miller, Salhi, & McLaughlin, 2020) developed the dimensional model of adversity and psychopathology (DMAP), emphasizing the unique signatures of two types of adversity: threat and deprivation. Threat-based adversities involve either direct or indirect harms, including sexual and physical abuse, as well as exposure to community violence.…”