Assessing within- and between-family variations in an expanded measure of childhood adversity.

Abstract

Previous measures of childhood adversity have enabled the identification of powerful links with later-life wellbeing. The challenge for the next generation of childhood adversity assessment is to better characterize those links through comprehensive, fine-grained measurement strategies. The expanded, retrospective measure of childhood adversity presented here leveraged analytic and theoretical advances to examine multiple domains of childhood adversity at both the microlevel of siblings and the macrolevel of families. Despite the fact that childhood adversity most often occurs in the context of families, there is a dearth of studies that have validated childhood adversity measures on multiple members of the same families. Multilevel psychometric analyses of this childhood adversity measure administered to 1,194 siblings in 500 families indicated that the additional categories of childhood adversity were widely endorsed, and increased understanding of the sources and sequalae of childhood adversity when partitioned into within- and between-family levels. For example, multilevel confirmatory factor analyses (MCFAs) indicated that financial stress, unsafe neighborhood, and parental unemployment were often experienced similarly by siblings in the same families and stemmed primarily from family wide (between-family) sources. On the other hand, being bullied and school stressors were often experienced differently by siblings and derived primarily from individual (within-family) processes. Multilevel structural equation modeling (MSEM) further illuminated differential criterion validity correlations between these categories of childhood adversity with midlife psychological, social, and physical health. Expanded, multidomain, and multilevel measures of childhood adversity appear to hold promise for identifying layered causes and consequences of adverse childhood experiences.

Confirmatory factor analysis of adverse childhood experiences (ACEs) among a community-based sample of parents and adolescents

“…This factor structure is not consistent with previous work, which may be due to the unrepresentative nature of the sample of low-income women as well as using eigenvalues lower than 1, which may overestimate the number of factors [35]. Finally, another study was conducted with a focus on differences among siblings in a sample of older adults (mean age = 59 years) and found evidence of different factor structures for within-family and between-family models [36]. As well, the samples used to generate the findings from these two latter studies were very specific (i.e., low income women and older sibling sample) and may have limited capacity to advance knowledge.…”

Coherence Between Feelings and Heart Rate: Links to Early Adversity and Responses to Stress

“…point before they turned 19. A previous study (Morrill et al, 2019) established a multilevel factor structure with 22 out of the 28 adverse events that was replicated in the present study (Fig. 3).…”

“…The binary nature of the childhood adversity data poses a computational challenge for MSEM (for more information, see Morrill et al, 2019). Bayesian estimation is an effective approach for modeling binary outcomes in multilevel confirmatory factor analysis (CFA) models (Muthén & Asparouhov, 2012).…”

“…Three hundred and five men and women from the Second Generation Study of the Harvard Study of Adult Development (Morrill et al, 2019) participated in an in-person laboratory visit. Of those 305, only those participants who completed stressful public speaking and mental arithmetic tasks during the lab visit (n = 279) were included in the present study.…”

The Youth and Childhood Adversity Scale: A step towards developing a new measure of adversity and its severity

“…Likewise, the Childhood Trauma Questionnaire (Bernstein & Fink, 1998;Bernstein et al, 1994) and its short version (Bernstein et al, 2003) are sound scales that measure more circumscribed family adversities. Recently, Morrill et al, 2019 contributed a comprehensive multidomain measure of EA tapping into within-and between-family sources of EA. However, many measures are quite exhaustive, resulting in long scales and complex factor solutions (e.g., the Assessing Environments III has up to 164 items; Berger et al, 1988).…”