OBJECTIVES

To examine the impact of cumulative adverse childhood experiences (ACEs) on a child’s foster care placement stability in Kansas.

METHODS

Secondary data analysis was conducted by using a purposive cohort sample of 2998 children, from 6 to 18 years old, in Kansas’s foster care system between October 2015 and July 2019. Multivariate hierarchical logistic regression models were used to examine the influence of cumulative ACEs on a child's placement stability. ACEs were measured at foster care intake and self-reported by the child. Placement stability variables were obtained through the state administrative database.

RESULTS

Children in foster care with greater cumulative ACE exposure were significantly more likely to experience placement instability. Compared to children with 1 to 5 ACEs, when controlling for all other variables, children with ≥10 ACEs had an increased odds of experiencing placement instability by 31% (odds ratio: 1.31; P < .05); and children with 6 to 9 ACEs had a 52% (odds ratio: 1.52, P < .001) increased odds of experiencing placement instability. A child’s race, biological sex, age at episode start, and whether they had siblings in foster care all significantly influenced placement instability.

CONCLUSIONS

Findings from this study, in conjunction with previous research on ACEs and foster care, highlight the need to proactively address ACEs and trauma exposure at foster care entry.

What’s Known on This Subject:

Children in foster care report amplified rates of ACEs, which significantly influences reunification outcomes. Despite the relevance of ACEs for the foster care population, little is known about the relationship between ACEs and placement stability.

What This Study Adds:

For children in foster care, ACEs were observed to significantly predict children’s placement instability. Effects were observed even after controlling for child-level variables.

Adverse childhood experiences (ACEs) have been identified as a critical public health issue among the pediatric population.1,2  Nationally, more than 1 in 5 US children (21.7%) report exposure to ≥2 ACEs,3  and recent research has demonstrated that children in foster care are at heightened risk of cumulative adversities, when compared with their nonfoster care counterpart.4,5  For children in foster care, ACEs have also been shown to negatively influence a child’s likelihood and time to reunification.6  Despite the relevance of ACEs among children in foster care, a scarcity of research exists examining children’s ACE exposure and its association with placement stability.

There is a growing body of evidence demonstrating the negative social, behavioral, physical, and neurologic developmental and well-being effects for children in foster care who experience placement instability.7  Specifically, placement instability has been associated with academic problems,8  internalizing and externalizing behaviors,9  and unhealthy attachments to caregivers,10  among others. Moreover, unstable or disruptions in placements while in foster care have been shown to deter the long-term goal of children exiting foster care to a permanent family.11 

Independently, placement instability9,11  and cumulative ACE exposure6  have been associated with negative health and well-being outcomes, along with decreased time to and likelihood of reunification for children in foster care. Despite the overlap in deleterious outcomes for this population, to the authors’ knowledge, no study has examined the influence of cumulative ACE exposure on a child’s foster care placement stability; with this study, we sought to fill this gap. We hypothesized children in foster care with higher cumulative ACE exposure would experience greater placement instability than their foster care counterpart with lower ACE exposure.

Researchers conducted secondary data analysis on a purposive sample of Kansas children in foster care. Original data were gathered as a component of a trauma-specific initiative funded by the Children’s Bureau; Administration on Children, Youth, and Families; and Administration for Children and Families. Kansas’ trauma initiative included integrating routine trauma and functional assessments at child welfare intake and various time points throughout care into the practices of the privatized foster care agencies. This initiative was a partnership between public child welfare, privatized foster care providers, and a public university. Data used were collected as a component of routine child welfare practice by the respective foster care providers. Protocol and protection for safeguarding human subjects protection were approved by the University of Kansas Institutional Review Board.

The study sample included 2998 children, between 6 and 18 years old, who entered foster care between October 1, 2015, and July 1, 2019, in Kansas. After entry into foster care, all children completed routine child welfare intake assessments with their caseworker who was trained in administration of the respective assessment. Assessment questions included exposure to adverse events and traumatic experiences. Children >6 years old at intake, per study protocols, self-reported their intake assessments. All children with complete ACE information (in total, 13 ACEs surveyed at intake) were eligible for inclusion. Thirty children were excluded because of incomplete ACE questions; the final sample included 2998 children in foster care. All data used in the current study were obtained through the agencies’ administrative data systems. Data included child-specific case information, such as child demographics and case characteristics.

Placement stability is a federal outcome required in the child and family service reviews, which is directly associated to a state’s child welfare funding, and serves as an important precursor for future foster care and child well-being outcomes. For these reasons, among others, the authors intentionally selected placement stability as the outcome of interest. Placement stability was standardized, using the following equation, by calculating a continuous annualized rate previously used in foster care literature12,13 :

AnnualizedPlacementRate(APR)=(#ofplacements#daysinfostercare)×365

The numerator included the total number of federal placement settings experienced by the child during their first removal episode in the study observation period. A child’s placements were summed following the federal definition of placements, which excludes temporary living conditions, such as respite care, camps, hospitalization, institutions, treatment facilities, and runaway episodes.14 

Given the skewness of the continuous annualized variable (ranged from 0.120 to 182.5; skewness = 8.45 [SE: 0.045]; kurtosis = 118.15 [SE: 0.089]), we transformed placement stability into a dichotomous variable; the cutoff was determined by observing the median value (2.46). Children with a placement stability annualized placement rate (APR) of 0 to 2.99 (coded “0”) were considered to have stable placements. Children with a placement stability APR of ≥3 (coded “1”) were considered to have experienced placement instability. This determination was guided by administrative policy put forth by the Children’s Bureau, which “…defines placement setting stability as a child having had 2 or fewer placement settings in a single foster care episode.”15 

The variable of interest for this study was cumulative ACE exposure. The researchers summed ACEs that were (1) identified through data fields in the administrative data set and (2) self-reported by the child during the routine child welfare intake assessment. The combination of ACE information was intentional, given the scarcity of research on the validity of child-reported ACEs, particularly among the foster care population. Researchers considered removal into foster care as an additional ACE; in total, 19 ACEs were included. Routine child welfare practice included assessment of 13 adverse events; children older than 6 years at the time of intake self-reported their exposure (“yes” was coded 1; “no” was coded 0) to the 13 surveyed adversities (wording is available on request). The administrative data set contained information on 12 ACEs, 7 of which overlapped with the ACEs assessed at intake. The researchers combined these 7 variables into one (see Table 1 for more information). For instance, if the administrative data set indicated the child was a victim of physical abuse and/or the child self-reported they were a victim of physical abuse then the researchers coded this as exposure (1) to physical abuse. All ACEs assessed at intake were developed and implemented as a competent of the local evaluation for Kansas’s trauma initiative. Table 1 identifies the 19 included ACEs and where they were obtained (ie, administrative data or self-reported intake assessment).

TABLE 1

ACEs and Associated Prevalence

ACEVariable NameFrequency (%)
Disastera 1337 (44.6) 
Accidenta 1445 (48.2) 
Personal hospitalizationa 1520 (50.7) 
Physical abusec 1831 (61.1) 
Sexual abusec 1568 (52.3) 
Intimate partner violencea 1513 (50.5) 
Neighborhood violencea 1436 (47.9) 
Foster care 2998 (100.0) 
Physical neglectc 2229 (74.3) 
10 Bullied and/or discriminationa 1460 (48.7) 
11 Parental mental health or substance use issuesc 2072 (69.1) 
12 Emotional abuse and isolationc 1483 (49.5) 
13 Parental loss or incarcerationc 1652 (55.1) 
14 Medical neglectb 0 (0.0) 
15 Abandonmentb 221 (7.4) 
16 Inadequate housingb 323 (10.8) 
17 Parental incapacityb 539 (18.0) 
18 “Other” trauma or victimizationc 1333 (44.5) 
19 Termination of parental rightsb 43 (1.4) 
ACEVariable NameFrequency (%)
Disastera 1337 (44.6) 
Accidenta 1445 (48.2) 
Personal hospitalizationa 1520 (50.7) 
Physical abusec 1831 (61.1) 
Sexual abusec 1568 (52.3) 
Intimate partner violencea 1513 (50.5) 
Neighborhood violencea 1436 (47.9) 
Foster care 2998 (100.0) 
Physical neglectc 2229 (74.3) 
10 Bullied and/or discriminationa 1460 (48.7) 
11 Parental mental health or substance use issuesc 2072 (69.1) 
12 Emotional abuse and isolationc 1483 (49.5) 
13 Parental loss or incarcerationc 1652 (55.1) 
14 Medical neglectb 0 (0.0) 
15 Abandonmentb 221 (7.4) 
16 Inadequate housingb 323 (10.8) 
17 Parental incapacityb 539 (18.0) 
18 “Other” trauma or victimizationc 1333 (44.5) 
19 Termination of parental rightsb 43 (1.4) 

N = 2998.

a

Self-reported ACE variable collected during routine child welfare agency intake assessment for all children ³6 y of age.

b

ACE variable obtained from administrative database.

c

ACE variable was surveyed at child welfare intake and available in administrative database and was combined by researchers into one variable.

A continuous ACE variable was created by summing the 19 ACEs; ACE scores could range from 1-19. The continuous variable was transformed into a 3-level categorical ACE variable: 1 to 5 ACEs (coded “1”), 6 to 9 ACEs (coded “2”), and ≥10 ACEs (coded “3”). Given the lack of theoretical and empirical guidance on ACE thresholds,7  the 3 categories were established on the basis of percentage distribution; each ACE category ranged between 22% and 41%.

Four covariates known to influence a child’s foster care placement experience were included: child’s race, biological sex, age at episode start, and siblings in foster care. Race has been identified as being a significant predictor of placement stability16  and was dichotomized because of high kurtosis values and separated into White (0) and non-White (1). Biological sex was only available as a dichotomous variable: female (0) and male (1). Age at episode start was transformed into 5 categories on the basis of child’s age at entry: ≤6 years (1); 6 to 9 years (2); 10 to 12 years (3); 13 to 15 years (4); and 16 to 18 years (5). Siblings in foster care was dichotomous: no (0) and yes (1). It is important to note ethnicity was excluded as a covariate from the respective analysis because inclusion of the variable slightly decreased model fit, was not significantly associated with placement stability, and did not affect the significance nor the magnitude of the relationships of the included study variables. The insignificant relationship between ethnicity and placement stability is corroborated by empirical literature.5 

Data analysis comprised univariate, bivariate, and multivariate analyses. All analyses were conducted in SPSS (IBM SPSS Statistics, IBM Corporation).17  Univariate analyses included observing frequencies and measures of central tendencies on all study variables. Simple bivariate logistic regressions were conducted first to examine the unadjusted relationships. Logistic regression was chosen because the predictor variables do not need to meet the assumption of normal distribution.18 

Multivariate hierarchical logistic regression models were used to answer how cumulative ACE exposure among children in foster care influenced placement stability. Hierarchical logistic regression was selected over other logistic regression methods because of the flexibility it permits in allowing researchers to determine the order of entering predictor variables into the analysis, based on theory, logic, and empirical research.18  Variables were entered into the analytic model on the basis of the ecological-transactional framework for ACE exposure and foster care involvement.5  In general, ontogenic child variables (ie, characteristics of the child) were entered in the first blocks proceeded by variables that changed over time and were influenced by external factors (ie, cumulative ACE exposure). See Liming5  for further details on application of the ecological-transactional model among children in foster care with ACEs.

Univariate and multivariate results are presented below. Because of space constraints and redundancy, bivariate results are not presented but are available on request. Bivariate models revealed statistically significant results and similar trends as the multivariate models between cumulative ACE exposure and placement stability.

All study variables had <0.5% missingness, and, therefore, no additional statistical methods were needed to account for missing data. Although there is no consensus among scholars on the best approach to compute sample size and power analyses for logistic regression,19  the authors conducted ad hoc power analyses in Stata/SE Version 15.120  (Stata Corp, College Station, TX) to examine the likelihood of multivariate logistic regression, by using the Wald test as the basis for computations, detecting specific effect size differences among the 2998 children in the study. With an α level of 0.05, the one-sided ad hoc power analysis illustrated sufficient power to detect small to large effect sizes for the respective study.

Youth in the sample were predominately White (80.8%), female (53.5%), and living in a family-type placement setting (86.4%) and had no siblings in foster care (57.3%). Forty-three percent of the sample experienced placement instability. Approximately 22% of the sample reported 1 to 5 ACEs, 40.8% reported 6 to 9 ACEs, and 37.4% reported ≥10 ACEs. Table 2 presents sample characteristics for the full sample and by ACE exposure categories (eg, 1 to 5 ACEs, 6 to 9 ACEs, and ≥10 ACEs). Sample characteristics were similar across the full sample and all 3 ACE subsamples.

TABLE 2

Sample Characteristics by Full Sample and Subsamples of ACE Categories

Full SampleSubsample With 1 to 5 ACEsSubsample With 6 to 9 ACEsSubsample With ≥10 ACEs
Total n (%) 2998 (100.0) 653 (21.8) 1223 (40.8) 1122 (37.4) 
Biological sex, n (%)     
 Male 1401 (46.7) 356 (54.5) 539 (44.1) 506 (45.1) 
 Female 1597 (53.5) 297 (45.5) 684 (55.9) 616 (54.9) 
Child’s age at episode start, mean (SD), y 12.1 (3.5) 11.7 (3.7) 12.4 (3.4) 12.0 (3.5) 
Age at episode start, n (%)     
 Early childhood: <6 y 102 (3.4) 43 (6.6) 30 (2.5) 29 (2.6) 
 Preadolescence: 6–9 y 842 (28.1) 188 (28.8) 309 (25.3) 345 (30.7) 
 Early adolescence: 10–12 y 674 (22.5) 152 (23.3) 280 (22.9) 242 (21.6) 
 Adolescence: 13–15 y 944 (31.5) 176 (27.0) 414 (33.9) 354 (31.6) 
 Older adolescence: 16–18 y 436 (14.5) 94 (14.4) 190 (15.5) 152 (13.5) 
Race, n (%)     
 White 2422 (80.8) 491 (75.2) 984 (80.5) 947 (84.4) 
 Non-White 576 (19.2) 162 (24.8) 239 (19.5) 175 (15.6) 
Siblings in FC,an (%)     
 No siblings in FC 1713 (57.3) 377 (57.7) 718 (58.7) 618 (55.1) 
 Siblings in FC 1274 (42.7) 274 (42.0) 500 (40.9) 500 (44.6) 
Last placement setting, n (%)     
 Family-type setting 2589 (86.4) 591 (90.5) 1047 (85.6) 951 (84.8) 
 Nonfamily-type setting 409 (13.6) 62 (9.5) 176 (14.4) 171 (15.2) 
Placement stability, n (%)     
 APR 0–2.99 (stability) 1697 (56.6) 412 (63.1) 639 (52.2) 646 (57.6) 
 APR ≥3.0 (instability) 1301 (43.4) 241 (36.9) 584 (47.8) 476 (42.4) 
No. placements 5.56 (9.1) 4.58 (8.3) 6.30 (10.0) 5.53 (8.4) 
Cumulative ACE exposure 8.3 (3.2) 3.9 (1.1) 7.6 (1.1) 11.8 (1.5) 
Full SampleSubsample With 1 to 5 ACEsSubsample With 6 to 9 ACEsSubsample With ≥10 ACEs
Total n (%) 2998 (100.0) 653 (21.8) 1223 (40.8) 1122 (37.4) 
Biological sex, n (%)     
 Male 1401 (46.7) 356 (54.5) 539 (44.1) 506 (45.1) 
 Female 1597 (53.5) 297 (45.5) 684 (55.9) 616 (54.9) 
Child’s age at episode start, mean (SD), y 12.1 (3.5) 11.7 (3.7) 12.4 (3.4) 12.0 (3.5) 
Age at episode start, n (%)     
 Early childhood: <6 y 102 (3.4) 43 (6.6) 30 (2.5) 29 (2.6) 
 Preadolescence: 6–9 y 842 (28.1) 188 (28.8) 309 (25.3) 345 (30.7) 
 Early adolescence: 10–12 y 674 (22.5) 152 (23.3) 280 (22.9) 242 (21.6) 
 Adolescence: 13–15 y 944 (31.5) 176 (27.0) 414 (33.9) 354 (31.6) 
 Older adolescence: 16–18 y 436 (14.5) 94 (14.4) 190 (15.5) 152 (13.5) 
Race, n (%)     
 White 2422 (80.8) 491 (75.2) 984 (80.5) 947 (84.4) 
 Non-White 576 (19.2) 162 (24.8) 239 (19.5) 175 (15.6) 
Siblings in FC,an (%)     
 No siblings in FC 1713 (57.3) 377 (57.7) 718 (58.7) 618 (55.1) 
 Siblings in FC 1274 (42.7) 274 (42.0) 500 (40.9) 500 (44.6) 
Last placement setting, n (%)     
 Family-type setting 2589 (86.4) 591 (90.5) 1047 (85.6) 951 (84.8) 
 Nonfamily-type setting 409 (13.6) 62 (9.5) 176 (14.4) 171 (15.2) 
Placement stability, n (%)     
 APR 0–2.99 (stability) 1697 (56.6) 412 (63.1) 639 (52.2) 646 (57.6) 
 APR ≥3.0 (instability) 1301 (43.4) 241 (36.9) 584 (47.8) 476 (42.4) 
No. placements 5.56 (9.1) 4.58 (8.3) 6.30 (10.0) 5.53 (8.4) 
Cumulative ACE exposure 8.3 (3.2) 3.9 (1.1) 7.6 (1.1) 11.8 (1.5) 

FC, foster care.

a

Missing 0.4% (n = 11 responses).

A hierarchical logistic regression was conducted to observe if children’s cumulative ACE exposure predicted placement stability, while controlling for race, biological sex, age at episode start, and siblings in foster care. Block 1 included children’s race and biological sex. Blocks 2 and 3 added categorical age at episode start and siblings in foster care covariates, respectively. Block 4 consisted of the independent variable, categorical cumulative ACE exposure. Table 3 presents the hierarchical logistic regression output for cumulative ACEs and placement stability.

TABLE 3

Hierarchical Logistic Regression Output: ACE Exposure and Placement Stability

Variableb (SE)OR95% CI
Block 1    
 Race [White] 0.20 (0.09) 1.22* 1.02–1.47 
 Biological sex [female] 0.07 (0.07) 1.08 0.93–1.24 
Block 2    
 Race [White] 0.20 (0.10) 1.22* 1.01–1.48 
 Biological sex [female] 0.15 (0.08) 1.16 0.99–1.35 
 Age at episode start    
  [Early childhood: <6 y] — — — 
  Preadolescence: 6–9 y 0.41 (0.26) 1.49 0.89–2.49 
  Early adolescence: 10–12 y 1.03 (0.26) 2.81*** 1.68–4.69 
  Adolescence: 13–15 y 1.55 (0.26) 4.73*** 2.85–7.85 
  Older adolescence: 16–18 y 1.92 (0.27) 6..81*** 4.02–11.54 
Block 3    
 Race [White] 0.23 (0.10) 1.26* 1.04–1.52 
 Biological sex [female] 0.16 (0.08) 1.18* 1.01–1.37 
 Age at episode start    
  [Early childhood: <6 y] — — — 
  Preadolescence: 6–9 y 0.40 (0.26) 1.50 0.89–2.50 
  Early adolescence: 10–12 y 1.02 (0.26) 2.76*** 1.65–4.62 
  Adolescence: 13–15 y 1.46 (0.26) 4.31*** 2.59–7.17 
  Older adolescence: 16–18 y 1.81 (0.27) 6.08*** 3.58–10.33 
 Siblings in FC [siblings in FC] −0.41 (0.08) 0.66*** 0.57–0.78 
Block 4    
 Race [White] 0.25 (0.10) 1.29** 1.06–1.56 
 Biological sex [female] 0.19 (0.08) 1.21* 1.03–1.41 
 Age at episode start    
  [Early childhood: < 6 y] — — — 
  Preadolescence: 6–9 y 0.34 (0.26) 1.41 0.84–2.36 
  Early adolescence: 10–12 y 0.95 (0.26) 2.59*** 1.55–4.35 
  Adolescence: 13–15 y 1.39 (0.26) 4.00*** 2.40–6.67 
  Older adolescence: 16–18 y 1.74 (0.27) 5.71*** 3.35–9.72 
 Siblings in FC [siblings in FC] −0.42 (0.08) 0.66*** 0.56–0.77 
Cumulative ACE exposure    
 [1–5 ACEs] — — — 
 6–9 ACEs 0.42 (0.11) 1.52*** 1.24–1.87 
 ≥10 ACEs 0.27 (0.11) 1.31* 1.06–1.61 
Variableb (SE)OR95% CI
Block 1    
 Race [White] 0.20 (0.09) 1.22* 1.02–1.47 
 Biological sex [female] 0.07 (0.07) 1.08 0.93–1.24 
Block 2    
 Race [White] 0.20 (0.10) 1.22* 1.01–1.48 
 Biological sex [female] 0.15 (0.08) 1.16 0.99–1.35 
 Age at episode start    
  [Early childhood: <6 y] — — — 
  Preadolescence: 6–9 y 0.41 (0.26) 1.49 0.89–2.49 
  Early adolescence: 10–12 y 1.03 (0.26) 2.81*** 1.68–4.69 
  Adolescence: 13–15 y 1.55 (0.26) 4.73*** 2.85–7.85 
  Older adolescence: 16–18 y 1.92 (0.27) 6..81*** 4.02–11.54 
Block 3    
 Race [White] 0.23 (0.10) 1.26* 1.04–1.52 
 Biological sex [female] 0.16 (0.08) 1.18* 1.01–1.37 
 Age at episode start    
  [Early childhood: <6 y] — — — 
  Preadolescence: 6–9 y 0.40 (0.26) 1.50 0.89–2.50 
  Early adolescence: 10–12 y 1.02 (0.26) 2.76*** 1.65–4.62 
  Adolescence: 13–15 y 1.46 (0.26) 4.31*** 2.59–7.17 
  Older adolescence: 16–18 y 1.81 (0.27) 6.08*** 3.58–10.33 
 Siblings in FC [siblings in FC] −0.41 (0.08) 0.66*** 0.57–0.78 
Block 4    
 Race [White] 0.25 (0.10) 1.29** 1.06–1.56 
 Biological sex [female] 0.19 (0.08) 1.21* 1.03–1.41 
 Age at episode start    
  [Early childhood: < 6 y] — — — 
  Preadolescence: 6–9 y 0.34 (0.26) 1.41 0.84–2.36 
  Early adolescence: 10–12 y 0.95 (0.26) 2.59*** 1.55–4.35 
  Adolescence: 13–15 y 1.39 (0.26) 4.00*** 2.40–6.67 
  Older adolescence: 16–18 y 1.74 (0.27) 5.71*** 3.35–9.72 
 Siblings in FC [siblings in FC] −0.42 (0.08) 0.66*** 0.56–0.77 
Cumulative ACE exposure    
 [1–5 ACEs] — — — 
 6–9 ACEs 0.42 (0.11) 1.52*** 1.24–1.87 
 ≥10 ACEs 0.27 (0.11) 1.31* 1.06–1.61 

N = 2,987. Data in brackets represent reference categories. —, represents reference category for respective variable.

*

P < .05.

**

P < .01.

***

P < .001.

Hierarchical regression results showed the model was statistically reliable at the P < .001 level (−2 log likelihood = 3807.91; χ2 (9) = 277.32; P < .001). Results indicated that cumulative ACEs were predictive of foster care placement stability or, rather, placement instability, when controlling for children’s race, biological sex, age at episode start, and if they had siblings in foster care. When all covariates were held constant, children who reported experiencing 6 to 9 ACEs had a 52% increased odds (odds ratio [OR]: 1.52; P < .001; 95% confidence interval [CI]: 1.24–1.87]) of having an APR >3, indicating placement instability, when compared with their foster care counterpart who reported cumulative ACE exposure of 1 to 5 adversities. Similarly, when compared with children who reported 1 to 5 ACEs and all other variables controlled, children in care with ≥10 ACEs had a 31% increased odds of experiencing placement instability (OR: 1.31; P < .05; 95% CI: 1.06–1.61).

Being non-White increased children’s odds of experiencing placement instability by 1.29 (OR: 1.29; P <.01; 95% CI: 1.06–1.56), when compared with their White counterpart and other variables held constant. Male children in foster care had a statistically significant increased odds of experiencing placement instability by 1.21 (OR: 1.21; P < .05; 95% CI: 1.03–1.56), compared with their female counterpart. Age at episode start significantly predicted placement stability, when controlling for all other factors. Compared with children who were <6 years old at episode start, children who were 10 to 12 years old at removal had a 259% increased odds of experiencing placement instability (OR: 2.59; P < .001; 95% CI: 1.55–4.35]); those 13 to 15 years old at removal had a 400% increased odds of experiencing placement instability (OR: 4.00 P < .001; 95% CI: 2.40–6.67]); and those 16 to 18 years old at removal had a 571% increased odds of experiencing placement instability (OR: 5.71 P < .001; 95% CI: 3.35 to 9.72]), when adjusting for all other variables. L astly, if a child had siblings in foster care, this decreased their odds of experiencing placement instability by 1.52 (OR: 0.66 [1/0.66 = 1.52]; P < .001; 95% CI: 0.56–0.77).

Findings revealed that children in foster care with greater cumulative ACE exposure have a significantly greater odds of experiencing placement instability. Additionally, high cumulative ACE exposure rates were observed among this foster care sample, corroborating previous research.4,6 

These findings are noteworthy for several reasons. First, placement instability has been shown to not only decrease a child’s likelihood of reunification but significantly influence a child’s likelihood of negative health and well-being outcomes,7  including substance use and risky sexual behaviors.21  Second, cumulative ACEs have been associated with a myriad of negative physical, behavioral, social, and neurological outcomes and, recently, has been shown to decrease a child’s likelihood of experiencing reunification.6  Considered in conjunction with previous literature, the findings from this study highlight the critical need of early ACE assessment and identification, specifically among an already vulnerable foster care population, recognizing that greater cumulative ACE exposure at intake can have deleterious implications on a child’s foster care placement experiences, which ultimately influences their chances of reunification.

Interestingly, children with 6 to 9 ACEs had a greater odds of experiencing placement instability than their counterpart who reported ≥10 ACEs. One potential reason for this finding is the age composition of this study’s sample; children who reported 6 to 9 ACEs were, on average, older at foster care entry (M = 12.4 years) than children who reported ≥10 ACEs (M = 12.0 years) and 1 to 5 ACEs (M = 11.7 years). Although it is a logical assumption that older children would report greater ACE exposure, a recent meta-analysis revealed that one of the strongest predictors of placement instability is older age at foster care entry, with the strongest predictor of placement instability being behavioral problems of the child,7  which, in this study, we were unable to control for. This finding may be unique to this study’s sample, and, therefore, future research is warranted to investigate and identify certain subgroups within the foster care population that may be disproportionately vulnerable to experiencing placement instability.

Another notable finding was that older, non-White, male children without siblings in foster care were significantly more likely to experience placement instability. This finding is consistent with other research finding that male children and children of color in Kansas were more likely to experience ≥3 foster care placements, compared with other states included in the study.22  Although the researchers do not want to overreach, these findings may reveal a subpopulation of children in foster care that may be disproportionately vulnerable to negative foster care placement experiences. These findings are concerning because they suggest systemic racism in the processes and procedures for child placements. Future qualitative studies, such as those conducted as institutional analyses,23  are needed to uncover the structural and policy mechanisms at play. S imilarly, future research investigating the effects of cumulative ACE exposure among certain subgroups of children in care, and how these subgroups of children may experience negative consequences and disparate outcomes, is needed. Specifically, a latent class analysis would allow researchers to examine the clustering-effects of ACEs for child demographics and placement characteristics.

This study had several strengths, including the child self-report of ACEs, incorporation of expanded ACEs, combination of self-reported and administrative data, and the use of a large, solely foster care sample. Despite the strengths, there are limitations worth noting. First, given the comorbidity of poverty, foster care, and ACE exposure, the inability for this study to control for family income or an adequate proxy is a substantial limitation. Data used in this study did not permit for controlling for previous foster care episodes, which previous research has shown to be significantly associated with placement instability.16,24  The use of point-in-time variables was also limiting and has the potential to be misleading. Specifically, point-in-time snapshot estimates of placement characteristics are often biased because of overrepresentation of children from different entry cohorts who remain in care for extended periods of time.8  A longitudinal, repeated-measure analysis following a specific entry cohort would be beneficial in examining how cumulative ACEs influence placement stability over time. Moreover, the authors recognize that the relationship between a child’s behavioral and developmental profiles, ACE exposure, and placement stability are complexly intertwined and untangling this relationship is difficult. The inability to control for developmental profiles and internalizing and externalizing behaviors is a limitation of this study because previous research has shown these behaviors are significantly related to increased ACE exposure25  and placement instability.7,26 

In addition, although a strength of the study, caution must be taken when using retrospective, self-reported data. It is likely that ACEs self-reported by the child do not accurately reflect their true ACE score for several reasons. First, intake assessments were completed in the presence of child welfare staff; for a variety of reasons, it is plausible that children may have downplayed or intentionally excluded disclosing ACE exposures for fear of prolonging their foster care stay or altering their case plan goal. Second, the intake assessment was not exhaustive, and additional ACEs may have been experienced by the child before foster care entry. Self-report responses are subject to the social desirability bias and telescoping effect, especially given the sensitive nature of the assessment. Because of study design, this sample was over-represented by older youth in care, given the age threshold of the self-report trauma measure; future studies should corroborate these findings with a younger population.

Moreover, foster care exposure and ACEs examined in this study could not be randomly assigned or amenable and, therefore, the results should be interpreted without assumptions of causation. This study should be replicated with other jurisdictions to consider whether findings generalize beyond Kansas. The findings from this study highlight the need for research to test the validity of child-reported ACE measures among vulnerable populations, such as children in foster care, especially given current federal regulations that require child welfare agencies to screen for trauma exposure.

Although the data used in this study were collected before 2020, it is important to acknowledge the impact the pandemic may have had on the study’s findings. On the basis of recent observations in this Midwestern state, the researchers hypothesize the pandemic would have improved placement stability for children in foster care because decreased mobility and increased concern for personal and public health were prioritized. Second, the pandemic has presented mental health challenges for many, and the authors speculate that, for children in foster care, these mental health issues were exacerbated. Thus, it is plausible that children in foster care with high ACEs would have experienced more challenges during the pandemic. However, it is difficult to know how analyses of cumulative ACEs and placement stability would look during the pandemic, given the decrease in placement moves.

Independently, ACEs and foster care involvement, along with placement instability, have been shown to have negative long-term health and well-being consequences. This current study builds on the independent literature bases by examining the impact of cumulative ACEs on a child’s foster care placement experiences. Considering this study’s results in light of existing research, practice and policy strategies may be needed to proactively address children’s experiences of adversity and trauma as they enter foster care. Findings from this study will aid policymakers, public health, social service, child welfare professionals, and the like in developing policies and practices that address and help mitigate the effects of ACEs on foster care outcomes.

We thank our community collaborators in this study: the Kansas Department for Children and Families, the Kaw Valley Center, and St Francis Community Services, Inc.

Dr Liming conceptualized the substudy, prepared the data, conducted data analysis, and drafted the initial manuscript; Dr Akin conceptualized and designed the parent study, facilitated selection and modification of data collection instruments, coordinated and supervised data collection, assisted with data preparation and data analysis, and reviewed and revised the manuscript; Dr Brook collaborated on the conceptualization of the study, assisted with oversight of data collection, and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspect of the work.

FUNDING: Study data were collected as a component of an initiative funded by the Children’s Bureau, Administration on Children, Youth and Families, Administration for Children and Families, US Department of Health and Human Services, under grant number 90CO1120. The article’s contents are solely the responsibility of the authors and do not necessarily represent the official views of the Children’s Bureau.

ACE

adverse childhood experience

APR

annualized placement rate

CI

confidence interval

OR

odds ratio

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose. This article is partially based on the dissertation completed by Liming (2020).

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits noncommercial distribution and reproduction in any medium, provided the original author and source are credited.