The effects of early life adversity on children’s mental health and cognitive functioning

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Abstract

Emerging evidence suggests that partially distinct mechanisms may underlie the association between different dimensions of early life adversity (ELA) and psychopathology in children and adolescents. While there is minimal evidence that different types of ELA are associated with specific psychopathology outcomes, there are partially unique cognitive and socioemotional consequences of specific dimensions of ELA that increase transdiagnostic risk of mental health problems across the internalizing and externalizing spectra. The current review provides an overview of recent findings examining the cognitive (e.g., language, executive function), socioemotional (e.g., attention bias, emotion regulation), and mental health correlates of ELA along the dimensions of threat/harshness, deprivation, and unpredictability. We underscore similarities and differences in the mechanisms connecting different dimensions of ELA to particular mental health outcomes, and identify gaps and future directions that may help to clarify inconsistencies in the literature. This review focuses on childhood and adolescence, periods of exquisite neurobiological change and sensitivity to the environment. The utility of dimensional models of ELA in better understanding the mechanistic pathways towards the expression of psychopathology is discussed, with the review supporting the value of such models in better understanding the developmental sequelae associated with ELA. Integration of dimensional models of ELA with existing models focused on psychiatric classification and biobehavioral mechanisms may advance our understanding of the etiology, phenomenology, and treatment of mental health difficulties in children and youth.

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Emotion-regulation strategies across psychopathology: A meta-analytic review.

Amelia Aldao, Susan Nolen-Hoeksema, Susanne Schweizer (2010)

We examined the relationships between six emotion-regulation strategies (acceptance, avoidance, problem solving, reappraisal, rumination, and suppression) and symptoms of four psychopathologies (anxiety, depression, eating, and substance-related disorders). We combined 241 effect sizes from 114 studies that examined the relationships between dispositional emotion regulation and psychopathology. We focused on dispositional emotion regulation in order to assess patterns of responding to emotion over time. First, we examined the relationship between each regulatory strategy and psychopathology across the four disorders. We found a large effect size for rumination, medium to large for avoidance, problem solving, and suppression, and small to medium for reappraisal and acceptance. These results are surprising, given the prominence of reappraisal and acceptance in treatment models, such as cognitive-behavioral therapy and acceptance-based treatments, respectively. Second, we examined the relationship between each regulatory strategy and each of the four psychopathology groups. We found that internalizing disorders were more consistently associated with regulatory strategies than externalizing disorders. Lastly, many of our analyses showed that whether the sample came from a clinical or normative population significantly moderated the relationships. This finding underscores the importance of adopting a multi-sample approach to the study of psychopathology. Copyright 2009 Elsevier B.V. All rights reserved.

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The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies.

Roman Kotov, Robert F. Krueger, David Watson … (2017)

The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures. (PsycINFO Database Record

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Cumulative risk and child development.

Gary Evans, Dongping Li, Sara Whipple (2013)

Childhood multiple risk factor exposure exceeds the adverse developmental impacts of singular exposures. Multiple risk factor exposure may also explain why sociodemographic variables (e.g., poverty) can have adverse consequences. Most research on multiple risk factor exposure has relied upon cumulative risk (CR) as the measure of multiple risk. CR is constructed by dichotomizing each risk factor exposure (0 = no risk; 1 = risk) and then summing the dichotomous scores. Despite its widespread use in developmental psychology and elsewhere, CR has several shortcomings: Risk is designated arbitrarily; data on risk intensity are lost; and the index is additive, precluding the possibility of statistical interactions between risk factors. On the other hand, theoretically more compelling multiple risk metrics prove untenable because of low statistical power, extreme higher order interaction terms, low robustness, and collinearity among risk factors. CR multiple risk metrics are parsimonious, are statistically sensitive even with small samples, and make no assumptions about the relative strengths of multiple risk factors or their collinearity. CR also fits well with underlying theoretical models (e.g., Bronfenbrenner's, 1979, bioecological model; McEwen's, 1998, allostasis model of chronic stress; and Ellis, Figueredo, Brumbach, & Schlomer's, 2009, developmental evolutionary theory) concerning why multiple risk factor exposure is more harmful than singular risk exposure. We review the child CR literature, comparing CR to alternative multiple risk measurement models. We also discuss strengths and weaknesses of developmental CR research, offering analytic and theoretical suggestions to strengthen this growing area of scholarship. Finally, we highlight intervention and policy implications of CR and child development research and theory. © 2013 American Psychological Association

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Author and article information

Contributors

Mark Wade:

ORCID: http://orcid.org/0000-0003-4643-8465

m.wade@utoronto.ca

Journal

Journal ID (nlm-ta): Transl Psychiatry

Journal ID (iso-abbrev): Transl Psychiatry

Title: Translational Psychiatry

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2158-3188

Publication date (Electronic): 10 June 2022

Publication date PMC-release: 10 June 2022

Publication date Collection: 2022

Volume: 12

Electronic Location Identifier: 244

Affiliations

GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Applied Psychology and Human Development, , University of Toronto, ; Toronto, ON Canada

Author information

Mark Wade http://orcid.org/0000-0003-4643-8465

Liam Wright http://orcid.org/0000-0002-6391-0197

Katherine E. Finegold http://orcid.org/0000-0001-6298-2802

Article

Publisher ID: 2001

DOI: 10.1038/s41398-022-02001-0

PMC ID: 9187770

PubMed ID: 35688817

SO-VID: ad6d7b28-8642-4360-b680-843530ad1069

License:

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