Capturing environmental dimensions of adversity and resources in the context of poverty across infancy through early adolescence: A moderated nonlinear factor model

Abstract

Income, education, and cumulative-risk indices likely obscure meaningful heterogeneity in the mechanisms through which poverty impacts child outcomes. The present study draws from contemporary theory to specify multiple dimensions of poverty-related adversity and resources, with the aim of better capturing these nuances. Using data from the Family Life Project (N=1,292), we leveraged moderated nonlinear factor analysis (MNLFA; Bauer, 2017) to establish group- and longitudinally-invariant environmental measures from infancy to early adolescence. Results indicated three latent factors—material deprivation, psychosocial threat, and sociocognitive resources—were distinct from each other and from family income. Each was largely invariant across site, racial group, and development and showed convergent and discriminate relations with age-twelve criterion measures. Implications for ensuring socioculturally-valid measurements of poverty are discussed.

Early Childhood Education and Care (ECEC) during COVID-19 boosts growth in language and executive function

“…Our data show that ECEC attendance during the pandemic boosts the growth of young children's emerging cognitive executive functions, regardless of their socioeconomic background. These benefits may be due to ECEC's provision of developmentally-appropriate learning materials and adult-child interactions which scaffold learning, and which have been shown to promote child EFs (46)(47)(48)(49). In pre-pandemic contexts, access to these EF-promoting factors in the home is greater for children of parents with higher-socioeconomic status (46,(48)(49)(50).…”

“…These benefits may be due to ECEC's provision of developmentally-appropriate learning materials and adult-child interactions which scaffold learning, and which have been shown to promote child EFs (46)(47)(48)(49). In pre-pandemic contexts, access to these EF-promoting factors in the home is greater for children of parents with higher-socioeconomic status (46,(48)(49)(50). Recent research indicates that engagement in enriching activities was not higher for more advantaged families during the 2020 pandemic (XXX masked for blinded review), which might explain why ECECbenefits extend across the socioeconomic spectrum.…”

What is an adaptive pattern of brain network coupling for a child? It depends on their environment

“…performance among the children living in poverty, we examined a number of demographic variables. While poverty status tends to be associated with a higher likelihood of particular experiences, such as racial or ethnic discrimination, more crowding in the home and financial strain, unsafe neighborhoods, and underfunded public schools, there is large variation in the experiences of children who live in poverty (DeJoseph et al, 2020). Moreover, experiences that are on average associated with worse cognitive outcomes (such as being deprived of caregiver support in early life) can, under some circumstances, produce better cognitive outcomes (Nweze et al, 2020), suggesting there may be different routes to achieving high cognitive performance in these cases.…”

“…Here, we seek to understand this form of resilience-high cognitive test performance in the face of structural barriers to success. One way to begin to address this question is to identify sets of experiences that may be protective for children in poverty, given the wide range of experiences they have (DeJoseph et al, 2020;Gonzalez et al, 2019). Another way is to probe differences in brain function, to gain insight into the mechanisms underlying resilience.…”

Treading Carefully: Agnostic Identification as the First Step of Detecting Differential Item Functioning

“…As a result, too-often DIF methods in applied research are at best ad hoc and at worst incorrect. As an example of the former, purification-the process of applying DIF methods in multiple iterations as opposed to in one-shot-is inconsistently used: Some recent applied DIF studies use it (Hagquist & Andrich, 2017;e.g, Teresi et al, 2009) while others do not (e.g., Crins et al, 2019;DeJoseph, Sifre, Raver, Blair, & Berry, 2020;Lopez-Vergara et al, 2020;Sheldrick et al, 2019)-and most do not give this potentially influential decision more than a sentence of consideration. Further, the majority of applied DIF studies neither acknowledge the assumptions on which their conclusions rest nor consider the possibility that their DIF detection process may not have worked properly.…”