Heterogeneity in caregiving-related early adversity: Creating stable dimensions and subtypes

Abstract

Early psychosocial adversities exist at many levels, including caregiving-related, extrafamilial, and sociodemographic, which despite their high interrelatedness may have unique impacts on development. In this paper, we focus on caregiving-related early adversities (crEAs) and parse the heterogeneity of crEAs via data reduction techniques that identify experiential cooccurrences. Using network science, we characterized crEA cooccurrences to represent the comorbidity of crEA experiences across a sample of school-age children (n = 258; 6-12 years old) with a history of crEAs. crEA dimensions (variable level) and crEA subtypes (subject level) were identified using parallel factor analysis/principal component analysis and graph-based Louvain community detection. Bagging enhancement with cross-validation provided estimates of robustness. These data-driven dimensions/subtypes showed evidence of stability, transcended traditional sociolegally defined groups, were more homogenous than sociolegally defined groups, and reduced statistical correlations with sociodemographic factors. Finally, random forests showed both unique and common predictive importance of the crEA dimensions/subtypes for childhood mental health symptoms and academic skills. These data-driven outcomes provide additional tools and recommendations for crEA data reduction to inform precision medicine efforts in this area.

Keywords: caregiving related early adversities; heterogeneity; prediction; subtyping.

Figure 1.

Full sample FA and PCA: (a) Factor analysis (FA). Caregiver-related early adversities (crEA) variables are shown on the y-axis, and variable loadings are shown across the first four principal factors on the x-axis. Note that the scree plot in E indicated that the first four were all significant. We labeled variables as unstable (blue) if the 95% confidence interval of the loading distribution across 1000 bootstraps included zero. We labeled variables as stable (red) when they did not. (b) Individual participant loadings on each of the FAs grouped by SL_group (DA = domestic adoption; DC = disrupted caregiving; PI = previous institutional care) (note: IFC was not included here due to small sample size. Dashed circle represents the sample average score. (c) Principal component analysis (PCA). Variable loadings of the first four components. Note that the scree plot in E indicated that the first two factors were significant. (d) Individual participant loadings on each of the FAs grouped by SL_group. Dashed circle represents sample average score. (e) Parallel analysis scree plot showing only the first two PCs have greater eigenvalues than the null distribution while the FA eigenvalues are greater than null for the first four factors. (f) Correlation matrix between the first four PCs and FAs. We see a very high correspondence (Pearson’s r = .899; r = .905) between the first two FA/PCs, respectively and moderate correlation between FA and PCs 3. Factor One: Additive Exposure. Factor Two: Emotional Maltreatment (without Domestic Violence) Factor Three: Physical/Supervisory Neglect. Sexual Abuse, Physical Abuse, and Emotional Abuse were all coded as either experiencing or witnessing through either TESI or MICM. Domestic Violence was coded as either experience or threat through either TESI or MICM. MICM = Maternal Interview of Childhood Maltreatment; TESI = Traumatic Events Screening Inventory.

Figure 2.

Subtyping. (a) Louvain community detection is used to find clusters of participants with similar exposure profiles to caregiver-related early adversities (crEAs). We show a correlation matrix across all participants. Yellow indicates two participants are highly similar in crEA exposure profiles. Cell(i,j) corresponds to the similarity in exposure profile between participant i and participant j. The topmost row color codes participants by their socio-legal groups SL(_groups) (DA: red, DC: green, PI: blue, IFC: purple), while column to the left of that color codes participants by their exposure profile cluster (Cluster 1: purple, Cluster 2: light blue; Cluster 3: brown; Cluster 4: yellow). Rows and columns are organized by hierarchical agglomerative clustering. Notably we see that all crEA profile clusters are made up of individuals from multiple SL_groups, demonstrating heterogeneity of adversities in each exposure environment. (b) Hierarchical clustering was applied to show how crEAs cluster together and how these crEAs clusters are distributed across the individual participants, across the crEAs profile clusters, and SL_groups. The Y-axis shows all crEAs, and the X-axis shows the crEAs scores (yellow=presence, purple=absence) for each individual participant. The topmost row color codes participants by their SL_groups, while the row underneath color codes participants by their crEA exposure profile cluster. Yellow indicates subjects are endorsed for a particular crEA. (c) We show how the four SL_groups are distributed across the four crEA profile clusters. (d) We show the intersubject correlations in crEA exposure profiles across the four SL_groups and crEA profile clusters. Sexual abuse, physical abuse, and emotional abuse were all coded as either experiencing or witnessing through either TESI or MICM. Domestic Violence was coded as either actual or threat through either TESI or MICM. MICM = Maternal Interview of Childhood Maltreatment; TESI = Traumatic Events Screening Inventory.

Figure 3.

crEA subtypes. (a) Factor 1: Additive Exposure; Factor 2: Emotional Maltreatment without Domestic Violence; Factor 3: Physical/Supervisory Neglect. Subtype 1 showed highest scores on Factor 3. Subtypes 2 and 3 showed low scores on Factor 3 and Factor 1 but higher than average scores on Factor 2. Subtype 4 had the highest scores on Factor 1 and lowest on Factor 2, suggesting high exposures to domestic violence. Subtype 5 showed second highest scores in the Factor 1 and Factor 3. The dashed circle indicates the sample average for each factor score. (b) We show how the five crEA subtypes loaded onto each of the individual crEA exposures. MICM = Maternal Interview on Child Maltreatment; TESI = Traumatic Events Screening Inventory. LOS-MICM = Lack of Supervision (MICM); Par-Sw = Parental Switches; DV-MICM/TESI = Domestic Violence – Threat or Actual (MICM/TESI); EA-MICM/TESI = Emotional Abuse (MICM/TESI); PA-MICM/TESI = Physical Abuse – Threat or Actual (MICM/TESI); SA-MICM/TESI = Experiencing and/or Witnessing Sexual Abuse (TESI); Par-Sub-Ab-TESI = Parental Substance Use/Abuse (TESI); Par-Ment-Ill-TESI = Parental Mental Illness (TESI); Par-Inc-TESI = Parental Incarceration (TESI); Par-Sep-TESI = Parental Separation (TESI); Par-Death-TESI = Parental Death (TESI); Par-Ill-Inj-TESI = Parental Illness or Injury (TESI); Em-Neg-MICM = Emotional Neglect (MICM); FTP-MICM = Failure to Provide (MICM). Sexual abuse, physical abuse, and emotional abuse were all coded as either experiencing or witnessing through either TESI or MICM. Domestic Violence was coded as either actual or threat through either TESI or MICM.

Figure 4.

The individual crEAs and FA scores were used to predict three key outcomes (CBCL Total Score, WIAT Reading percentile, and WIAT Numbers percentile) in the sample using Random Forest. Each plot shows the ranking of variable importance in making the prediction in out-of-bag data. Note: Caregiver Education and Household Income reflect current values. Sexual abuse, physical abuse, and emotional abuse were all coded as either experiencing or witnessing through either TESI or MICM. Domestic Violence was coded as either actual or threat through either TESI or MICM.

Figure 5.

(a) We show the performance of SL_groups and crEA subtypes with and without adding in SES variables (Current Household Income, Parental Years of Education) in predicting CBCL, WIAT Numbers and WIAT Reading. (b) Distributions of crEA subtypes relative to a comparison group without crEA exposure across the three outcomes variables. ANOVA comparing comparison group to all crEA subtypes p < .0001 (***). (c) Variable importance values for each of the individual crEA subtypes in RF predictions with current SES. CBCL = Child Behavior Checklist; WIAT = Wechsler Individual Achievement.