Profiles of Domain-Specific Cognitive Development in Socioeconomically Diverse Youth

• In Event: Socioeconomically Diverse Families Contain Multitudes: Strengths-Based Approaches to Cognitive Development

Abstract

Research using variable-centered approaches has consistently reported associations between access to socioeconomic resources (SER) and impairments in youth cognitive outcomes (Farah et al., 2006). However, far fewer studies have sought to identify person-centered patterns of cognitive resilience (CR) to low SER. Emerging evidence suggests that cognitive development in low-SER youth may be non-uniform across cognitive domains (Ellis et al., 2020). For example, although numerous studies report that youth living in poverty perform worse on working memory tasks compared to their high-SER peers (Dang et al., 2016; Mani et al., 2013), youth from low SER backgrounds have also been found to perform well on procedural learning tasks. Additionally, the factors that promote CR across ecological domains (i.e., family, neighborhood, and school) are unclear, though several physical and social exposures (e.g., supportive peers) are theorized based on studies of youth resilience to other forms of adversity (e.g., maltreatment; Masten, 2014).

The current study aims to identify SER-dependent cognitive profiles using data from the population-based Adolescent Brain Cognitive Development study (N = 9,839; ages 9 – 11). We used confirmatory factor analysis to fit two latent factors of SER across family and neighborhood contexts. Model fit was excellent (RMSEA = 0.025, CFI = 0.976) with higher factor scores reflecting greater SER. Ten measures of cognitive function (e.g., NIH Toolbox Flanker task, Rey auditory verbal learning test) were fit as a 3-factor model to include verbal/spatial (V/S), speed/flexibility (S/F), and memory latent factors, with good model fit (RMSEA = 0.082, CFI = 0.925).

We leveraged a person-centered perspective (i.e., latent class analysis) to identify SER-dependent cognitive profiles. A 4-class solution was identified with acceptable model fit (Entropy = 0.703). First, a “disadvantaged, at-risk” profile (2.9%, n = 287) was characterized by low SER and the lowest cognitive domain scores (i.e., 1.3-2.34 SD below sample means). Second, an “average-average” profile (36.7%, n = 3,611) was characterized by average SER scores (i.e., statistically indistinguishable from sample means) and average cognitive domain scores (i.e., only 0.11-0.18 SD above sample means). Third, an “advantaged” profile (37.8%, n = 3,716) was characterized by high SER and above average cognitive function (i.e., 0.25-0.39 SD). Lastly, a large profile of “cognitively resilient” youth (22.6%, n = 2,225) was characterized by the lowest SER and slightly below average cognitive performance (i.e., 0.37-0.62 SD below sample means).

As expected, we identified profiles of “disadvantaged-risk”, “advantaged”, and “average-average” youth based on their neighborhood and family SER and cognitive performance. However, almost a quarter of the study sample was characterized as “cognitively resilient”; despite having the lowest SER of the sample, these youth performed close to the sample average on measures of speed/flexibility, verbal/spatial, and memory. Further analyses will use ridge regression to identify predictors of profile membership across neighborhood, school, family, and individual contexts.

Although much literature has leveraged variable-centered approaches to study cognitive performance in the context of socioeconomic disadvantage, the current study points to person-centered approaches as a means to identify meaningful variability in how youth adapt in the face of socioeconomic risk.

Authors

• Deena Ahmad Shariq, University of Maryland - College Park
  Presenting Author

• Rachel R. Romeo, University of Maryland - College Park

• Arianna Gard, University of Maryland - College Park