| Literature DB >> 35317011 |
Clancy Blair1,2, Seulki Ku1.
Abstract
We present a hierarchical integrated model of self-regulation in which executive function is the cognitive component of the model, together with emotional, behavioral, physiological, and genetic components. These five components in the model are reciprocally and recursively related. The model is supported by empirical evidence, primarily from a single longitudinal study with good measurement at each level of the model. We also find that the model is consistent with current thinking on related topics such as cybernetic theory, the theory of allostasis and allostatic load, and the theory of skill development in harsh and unpredictable environments, referred to as "hidden talents." Next, we present literature that the integrative processes are susceptible to environmental adversity, poverty-related risk in particular, while positive social interactions with caregivers (e.g., maternal sensitivity) would promote self-regulatory processes or mitigate the adverse effect of early risk on the processes. A hierarchical integrative model of self-regulation advances our understanding of self-regulatory processes. Future research may consider broader social contexts of the integrative self-regulation system, such as neighborhood/community contexts and structural racism. This can be an integral step to provide children with equitable opportunities to thrive, even among children living in socioeconomically and psychosocially disadvantaged environments.Entities:
Keywords: behavior regulation; emotion regulation; executive function; genetics; physiological regulation; self-regulation; stress
Year: 2022 PMID: 35317011 PMCID: PMC8934409 DOI: 10.3389/fpsyg.2022.725828
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Figure 1A hierarchical integrated model of self-regulation in which cognitive, emotional, behavioral, physiological, and genetic levels of self-regulation are reciprocally and recursively related. In this view, executive function is the cognitive component at the highest level of the integrated model.