Service Receipt and Mental Disorders in Child Welfare and Mental Health Systems in Los Angeles County

Children involved in the child welfare (CW) system are at higher risk of mental health problems and poorer mental health outcomes compared with other subpopulations of children in the United States (1,2). Risk factors that often co-occur with child maltreatment, including exposure to trauma, place additional stressors on children’s mental health (3,4). Although an extensive literature has examined the prevalence of symptoms and behaviors associated with mental illness in this population (5–7), little is known about the prevalence of specific mental disorders, especially as it relates to mental health service receipt (8). A possible reason is that CW and mental health agencies operate in different jurisdictions and diagnostic information is not generally shared between systems. However, increased interagency collaboration between CW and mental health agencies may help bridge this information gap (7,9).

A previous study described the legal context and organizational processes of collaboration between Los Angeles County’s Department of Children and Family Services (DCFS) and Department of Mental Health (DMH)—the two largest CW and mental health service agencies in the United States (10). The study reported here strived to address gaps in the literature by using merged administrative data to examine the presence of mental disorders and correlates of specific service receipt by various DSM-IV-TR diagnostic classifications (11). The use of merged administrative data provided a unique opportunity to more closely examine the mental health needs of children dually served by CW and mental health systems in a region of the country with a racially and ethnically diverse population.

The presence of greater mental health needs in the CW population has been well established. However, most research on CW-involved children has used the Child Behavior Checklist (CBCL) to estimate the prevalence of mental health needs (5,6). Because the CBCL is a symptom- and behavior-based measure and not a diagnostic instrument, its ability to identify specific mental disorders is limited. Consequently, few studies have been able to explore the relationship between demographic and CW-related characteristics and diagnostic classifications (for example, DSM-IV-TR diagnoses) (8). The few that have explored diagnostic classifications for CW-involved children found that rates of specific mental disorder diagnoses varied according to gender, race-ethnicity, and placement type (8,12). One study found that black youths were less likely than white youths to be diagnosed as having major depression and that youths in kinship foster care were less likely than youths in out-of-home placement to meet diagnostic criteria (8). Existing research that used the CBCL indicated that youths from racial-ethnic minority groups were less likely to receive mental health services (13) and that language barriers contributed to less accurate assessments (14). CW characteristics, such as out-of-home placement and maltreatment type, have also been shown to be associated with an increased likelihood of treatment receipt (5,13). Research also found that children with attention-deficit hyperactivity disorder (ADHD) and behavior disorders had higher rates of service receipt than children without these disorders and that rates of disruptive disorders were lower among Hispanic adolescents compared with white adolescents (15,16).

Because of the limited literature on the prevalence and correlates of service receipt by diagnostic classifications for CW-involved children, this study aimed to describe the presence of mental illness–related diagnostic classifications and examine the relationship between sociodemographic and CW-related characteristics and outpatient service receipt by diagnostic classification. Specifically, to provide a window into treatment intensity and approaches for children with various DSM-IV-TR diagnoses, we examined service receipt as measured by the number of therapeutic services received and receipt of specific services, including individual and family therapy. On the basis of existing literature (17) and research on extensive trauma experienced by CW-involved children (3,4), we expected to find higher rates of DSM-IV-TR diagnoses overall among these children, compared with children in the general population, especially trauma-related diagnoses. Findings will increase understanding of profiles of service receipt among children dually served by CW and mental health agencies. Development of such profiles can generate targeted action priorities for service delivery and guide prevention and intervention efforts for this vulnerable population (18).

Methods

Data

This study used DCFS and DMH administrative data. Between July 2011 and July 2012, a total of 4,694 children with substantiated cases of child maltreatment were identified by CW staff members as needing mental health services. This study included the 3,191 children who were referred to DMH and subsequently received an assessment for presence of mental illness–related diagnosis by licensed mental health specialists (for example, psychiatrists, doctoral-level psychologists, and licensed therapists). The University of Southern California Institutional Review Board and the Human Subject Research Committee at DMH reviewed and approved this study.

Measures

Demographic variables.

Demographic characteristics consisted of gender, age, race–ethnicity, and language. Age was grouped as 0–5, 6–10, 11–14, and ≥15; race-ethnicity was grouped as white, black, Hispanic, and other. Maltreatment types included neglect, emotional abuse, physical abuse, sexual abuse, and risk due to sibling abuse. Spanish as primary language, history of out-of-home placement, and previous history of mental health treatment from DMH were dichotomous variables (yes or no).

DSM-IV-TR mental disorder diagnoses.

Diagnoses were categorized into four major classes: mood disorders (presence of depression and bipolar disorder), anxiety disorders (anxiety and posttraumatic stress disorder), ADHD, and behavior disorders (oppositional defiant disorder and conduct disorder) (11). DSM-IV-TR diagnostic classifications were dichotomous variables (diagnosis versus no diagnosis).

Dependent variables.

Outpatient service receipt was measured by the number of unique therapeutic interventions received (20 interventions were included; for example, psychiatric diagnostic services, therapy, and case consultation). In addition, we measured receipt of individual therapy (yes or no) and family therapy (yes or no) services.

Analyses

Distribution of the continuous dependent variable and missing data patterns were assessed. Regarding the number of services received, the kurtosis value (4.18) fell outside the acceptable range of <3.0 (absolute value; skew=.98) (19) and a square-root transformation was performed (skew=.11; kurtosis=2.75). Variance inflation factors for all variables were <3, suggesting no multicollinearity issues (20).

Univariate and bivariate analyses were conducted to derive descriptive statistics. Multivariate ordinary-least-squares linear regression models were fitted to examine the relationship between sociodemographic and CW-related characteristics and the number of services received by diagnostic classifications. Multivariate logistic regression models were conducted for each diagnostic classification to examine the relationship of sociodemographic and CW-related characteristics and receipt of individual and family therapy services. Data were missing for 6% (N=196) of the children in the overall sample and for 9% (N=85, mood disorders), 5% (N=34, anxiety disorders), 12% (N=35, ADHD), and 8% (N=23, behavior disorders) of the children for whom data were included in the models. Complete case analyses were used because there was insufficient information available to reasonably impute the data, resulting in the following final sample sizes: mood disorders, N=871; anxiety disorders, N=597; ADHD, N=256; and behavior disorders, N=277. Chi-square, R², and Hosmer-Lemeshow (group number of 10) tests for logistic regression were used to examine model fit (21,22). Analyses were conducted with Stata 13.

Results

Descriptive and Bivariate Analyses

Table 1 presents descriptive statistics for the total sample (N=3,191) and for children in the four diagnostic classifications. Among these children, 68% (N=2,178) met criteria for one of the four diagnostic classifications. Mood disorders were the most common (30%), followed by anxiety disorders (20%), behavior disorders (9%), and ADHD (9%). For the overall sample, the mean number of therapeutic services received was 2.65; 38% of the children received individual therapy, and 12% received family therapy.

Multivariate Regression

Results of analyses of the number of therapeutic services received by diagnostic classification are presented in Table 2. We found significant relationships between age and number of therapeutic services received for each classification. Children ages 0–5 received significantly fewer therapeutic services than youths ages ≥15 (mood disorders, β=–.30, t=–2.58, df=13, p=.01; anxiety disorders, β=–.53, t=–5.82, df=13, p<.001; ADHD, β=–.45, t=–2.51, df=13, p=.01; and behavior disorders, β=–.63, t=­3.69, df=13, p<.001). In addition, history of out-of-home placement was positively associated with the number of therapeutic services received for mood disorders (β=.21, df=13, t=3.59, p<.001), anxiety disorders (β=.19, df=13, t=3.02, p<.001), and behavior disorders (β=.29, df=13, t=3.12, p<.001). Previous involvement with DMH was positively associated with the number of therapeutic services received for mood disorders (β=.74, df=13, t=12.49, p<.001), anxiety disorders (β=.44, df=13, t=7.40, p<.001), ADHD (β=.64, df=13, t=5.50, p<.001), and behavior disorders (β=.66, df=13, t=6.02, p<.001).

Multivariate Logistic Regression Models

Table 3 and Table 4 present model fit statistics and the odds of receiving individual therapy and family therapy services, respectively, by DSM-IV-TR classification.

Mood disorders and individual therapy.

As shown in Table 3, for children with mood disorder diagnoses, younger children were less likely than youths ages ≥15 to receive individual therapy (ages 11–14, OR=.67; ages 6–10, OR=.45; ages 0–5, OR=.30). In addition, children with previous DMH involvement had greater odds than those without previous involvement of receiving individual therapy services (OR=3.29).

Anxiety disorders and individual therapy.

Younger children with anxiety disorder diagnoses were less likely than youths ages ≥15 to receive individual therapy (ages 6–10, OR=.33; ages 0–5, OR=.19). Children with previous DMH involvement had greater odds than those without previous involvement of receiving individual therapy services (OR=1.84).

ADHD and individual therapy.

Among children with an ADHD diagnosis, younger children were less likely than youths ages ≥15 to receive individual therapy (ages 6–10, OR=.31; ages 0–5, OR=.24). Those who had experienced out-of-home placement had lower odds of receiving individual therapy services (OR=.41), compared with those who had not experienced out-of-home placement. In contrast, those who had previous DMH involvement had greater odds of receiving individual therapy services, compared with those who had no previous involvement (OR=7.09).

Behavior disorders and individual therapy.

Compared with youths ages ≥15, children ages 0–5 with a behavior disorder diagnosis had decreased odds of receiving individual therapy (OR=.30). In addition, children with previous DMH involvement had greater odds than those with no previous involvement of receiving individual therapy services (OR=3.07).

Mood disorders and family therapy.

As shown in Table 4, among children with mood disorder diagnoses, those ages 0–5 were more likely than those ages ≥15 to receive family therapy (OR=5.58). In addition, children with previous DMH involvement had greater odds than those without previous involvement of receiving family therapy (OR=2.44).

Anxiety disorders and family therapy.

Children ages 0–5 with an anxiety disorder diagnosis were more likely than youths ages ≥15 to receive family therapy (OR=2.07). In addition, those with previous DMH involvement had greater odds than those without previous involvement of receiving family therapy (OR=2.51).

ADHD and behavior disorders and family therapy.

None of the results in the ADHD model were statistically significant; model fit statistics for the behavior disorders model indicated a poor fit, and results were not interpreted (21,22).

Discussion

This study contributed to the literature by describing outpatient mental health service receipt outcomes of children served by collaborating CW and mental health service systems in Los Angeles County. This is one of a few studies to examine discrete diagnostic categories and outcomes, rather than problem behaviors and symptomatology, among all CW-involved children, not just those in foster care (12,23,24).

The unique mental health needs of CW-involved children are exemplified by the differences in diagnostic rates for this sample and for children in the general population. In this study, the most common diagnosis was mood disorders (30%), followed by anxiety disorders (20%), behavior disorders (9%), and ADHD (9%). In national samples of children in the general population, ADHD is the most common diagnosis (9%), followed by behavior disorders (3%), anxiety (3%), and depression (2%) (17). This finding supports existing literature that found high mental health needs in this population. However, there may be fundamental differences in how mental health practitioners assess CW-involved children. For example, because of the high need and risk in this population, mental health practitioners may inflate diagnoses of CW-involved youths to ensure that they meet qualifications for receipt of appropriate services (25–27). In a study of youths in foster care, ADHD was the most common diagnosis (16%), followed by depression (15%), behavior disorders (8%), and anxiety disorders (7%) (23). Further exploration of differences in the prevalence of mental disorder diagnoses between children in foster care and those not in out-of-home placements is warranted.

Findings related to age and the number of therapeutic services received are also commensurate with findings in other CW samples (28,29). Overall, we found a significant relationship between age and the number of therapeutic services received, with older children receiving more services. This finding is concerning because 21% of children who enter the CW system do so before they are a year old (30), and early diagnosis and appropriate mental health treatment is crucial for long-term outcomes (2,17). However, this finding is not surprising given that older youths in the CW system tend to have more severe mental health challenges; thus they have greater need for more intensive services because they are also more likely to have been in the system longer and to have had a greater number of traumatic experiences, transitions in households, losses, and so forth.

Our study also found that children who had previous involvement with DMH received more services regardless of their diagnosis. This finding speaks to the chronic nature of mental health needs and the importance of early intervention for this population. Our findings departed from those of other studies of CW-involved youths that identified racial and ethnic disparities in the receipt of mental health services (28,29). Race-ethnicity did not play a significant role in predicting service receipt in our study, except among children who identified as other (not black, Hispanic, or white). One plausible explanation is that collaboration between DCFS and DMH may have promoted screening for and identification of mental health needs in our sample, which may have facilitated linkages to services and ameliorated racial and ethnic disparities in service receipt. This explanation is supported by other studies that have found that collaboration reduces racial and ethnic disparities in service receipt in CW-involved populations (7,9).

In terms of specific types of services received (individual or family therapy), younger children received fewer individual therapeutic interventions regardless of whether they had a diagnosis of a mental disorder. Although it may be clinically most appropriate to channel young children into family therapy, individual interventions should not be overlooked as an important treatment option. Family therapy can be challenging for families experiencing disruption related to CW involvement, and it may be difficult to engage emergency guardians in family therapy if the child will be removed from that placement after a brief period. Future studies should look at the efficacy of individual versus family therapy for CW-involved children, particularly cases of temporary or emergency placement.

Of additional concern is that children with a diagnosis of ADHD who were in out-of-home placements were less likely to receive individual therapy than those who were not in such placements. Although it is difficult to engage children in out-of-home placements in mental health treatment because of placement disruptions and changing caregivers, children with ADHD are vulnerable to placement disruptions because of their behavior needs (for example, externalized or internalized behaviors) (31). Future research should examine whether lower levels of individual treatment for children with ADHD in out-of-home placements contribute to increased placement instability and mental health problems.

This study was unable to ascertain the quality and length of services received or the receipt of other types of services (for example, inpatient services). Information on specific services offered or available to each age group was also unavailable. We were also unable to account for other factors (for example, family engagement, legal dynamics, and child development) that may have influenced the receipt of mental health services. Findings could have been strengthened by the availability of information on how diagnosis were assigned to the children. In addition, data on diagnoses of other mental disorders (for example, eating disorders) and receipt of psychotropic medications were not available. Finally, model fit statistics for some of the models examining receipt of family therapy indicated moderate to poor fit to the data, and the results should be interpreted cautiously (21,22).

Conclusions

By identifying correlates of mental health service receipt among CW-involved children in specific diagnostic classifications of mental disorders, we can develop targeted action priorities in the delivery of more nuanced mental health services. Identification also allows mental health service sectors to select and train staff members on the interventions most relevant for the populations they serve. For example, in our sample, most children had a diagnosis of mood disorders as opposed to ADHD, which is the most prevalent disorder among children in the general population. Thus mental health agencies with large CW caseloads may choose to invest in training in evidence-based practices for mood disorders, such as cognitive-behavioral therapy or Incredible Years (32), rather than in other, less applicable interventions.