J Abnorm Child Psychol DOI 10.1007/s10802-015-9998-6
Symptom Trajectories Among Child Survivors of Maltreatment: Findings from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN) Dean Lauterbach & Cherie Armour
# Springer Science+Business Media New York 2015
Abstract Very few studies have investigated the longitudinal trajectory of depression and anxiety related symptomatology among child victims of maltreatment or among those at risk for maltreatment. The current study examined latent class trajectories of anxiety/depression symptoms in a sample of 1354 (n=657 boys, n=697 girls) victimized or at risk children using data collected from the Longtitudinal Studies of Child Abuse and Neglect (LONGSCAN). Four trajectory groups were identified labeled low-stable, moderate-stable, moderate-increasing, and high-decreasing. This study also sought to investigate predictors of group membership. Relative to the lowstable group, membership in the three more pathological groups (i.e., moderate-stable, moderate-increasing, and highThe data used in this publication were made available by the National Data Archive on Child Abuse and Neglect, Cornell University, Ithaca, NY, and have been used with permission. Data from Longitudinal Studies of Child Abuse and Neglect (LONGSCAN) Assessments 0–14 were originally collected by Desmond K. Runyan, Howard Dubowitz, Diana J. English, Jonathan Kotch, Alan Litrownik, Richard Thompson and Terri Lewis & The LONGSCAN Investigator Group. Funding for the project was provided by the Office on Child Abuse and Neglect (OCAN), Children’s Bureau, Administration for Children and Families, Dept. of Health and Human Services (The National Center on Child Abuse and Neglect (NCCAN), under the Office of Human Services funded this consortium of studies during the early years of data collection from 04/ 01/1991 until NCCAN became part of OCAN in 1998.) The collector of the original data, the funder, NDACAN, Cornell University and their agents or employees bear no responsibility for the analysis or interpretations. D. Lauterbach (*) Department of Psychology, Eastern Michigan University, 303a Mark Jefferson Science Hall, Ypsilanti, MI 48197, USA e-mail: [email protected] C. Armour School of Psychology, University of Ulster at Coleraine Campus, Coleraine, Northern Ireland, UK
decreasing) was predicted by a greater number of maltreatment allegations, more visits to a primary care physician for psychological issues, less perceived support by primary maternal caregiver, and lower rated popularity of the child. Implications for early identification of child maltreatment victims in primary health care settings was discussed. Keywords Child maltreatment . Longitudinal . Growth mixture modeling
The experience of childhood physical, sexual, or emotional abuse has significant long term consequences. These consequences were summarized by Gilbert et al. (2009), who note that 25 % to 30 % of maltreated children meet criteria for major depression by their late 20s and 17 % to 23 % of maltreated children meet criteria for PTSD in their late 20s. However, in a controversial meta analysis (Rind, Tromovitch, and Bauserman 1998) it was concluded that child sexual abuse victims are best characterized as being only Bslightly less well-adjusted than controls^ long term (Rind et al. 1998, p. 22). While a critical examination of this meta-analysis called into question some of the study’s conclusions (cf. Dallam, Gleaves, Cepeda-Benito, Silberg, and Kraemer 2001) it is readily apparent that the longitudinal course of psychopathological symptoms among child maltreatment victims is an area of considerable interest. The substantial differences in findings suggests variability in symptom trajectories that is obscured using traditional analytic techniques. Conventional approaches to modeling the longitudinal course of symptoms assume that individuals are sampled from a single population and that a single growth trajectory will adequately describe the entire population. However, anecdotal clinical observations and empirical
J Abnorm Child Psychol
research suggest the presence of subgroups characterized by differences in change over time. Growth mixture modeling (GMM) is a person-centered statistical technique that allows for the identification of homogenous groups (classes) of children based on symptom trajectory (B. Muthén 2004; Nagin 2005). Therefore, it is possible to identify latent classes of maltreated children whose symptoms display differential trajectories over time. In addition, it is possible to examine potential predictors of group membership and thus trajectory. This stands in contrast to variable-centered approaches that describe covariation among variables. Person-centered approaches are better suited to addressing individual differences in patterns of change over time (Laursen and Hoff 2006). Therefore, this paper will utilize GMM to examine the number, shape, and predictors of anxious/depressed symptom trajectories in a sample of children who were either abused or at elevated risk for abuse. The literature review that follows will discuss studies in the trauma field that have utilized GMM in examining the psychopathological symptom trajectories of child maltreatment victims and potential predictors of trajectory classes. Special attention will be devoted to studies examining internalizing symptom trajectories.
Symptom Trajectories Among Child Maltreatment Victims Several recent studies have examined the heterogeneity of symptom change among child (Kim, Cicchetti, Rogosch, and Manly 2009; Proctor, Skriner, Roesch, and Litrownik 2010; Tabone et al. 2011; Woodruff and Lee 2011) and child/adolescent (Nugent et al. 2009; Thompson et al. 2011) maltreatment victims. In the majority of studies, either the Externalizing or the Internalizing broad-band scale of the Child Behavior Checklist (CBCL: Achenbach 1991) was one of the dependent variables. The lone exception was Nugent et al. (2009) which assessed PTSD symptomatology. Findings from these studies differ markedly in the number of trajectories that best characterize the sample. Three studies of child and child/adolescent victims of maltreatment identified relatively little heterogeneity in symptom change over time with the number of classes ranging from one to three. Subjects in these studies have included children/ adolescents who were referred to the U.S. Navy’s Family Advocacy Program because of allegations of child sexual abuse, child physical abuse, or intimate partner violence (Nugent et al. 2009), maltreated children who had attended a summer day camp research program (Kim et al. 2009), and maltreated children who had spent at least 5 months in out-ofhome foster care (Proctor et al. 2010). Nugent et al. (2009) concluded that a linear two-class model provided the best fit to the data. One class was characterized by minimal symptoms across assessment frames with a slight increase over time
whereas the second class was characterized by moderately high symptoms at initial assessment which were relatively stable over time. Children in this study (N=201) ranged in age from 7 to 18 and were followed for 40 months. Kim et al. (2009) concluded that a two-class solution best characterized the personality characteristic ego resiliency among maltreated children. Ego resiliency refers to the ability to flexibly use problem solving strategies that are well suited to changing circumstances (Block and Block 1980) and high ego resiliency is predictive of low internalizing symptoms (Cicchetti and Rogosch 1997). One group had increasing levels of ego resiliency between ages 7 and 10 and the second had consistently decreasing levels of this characteristic. This same study found that a one-class solution best characterized externalizing symptoms, internalizing symptoms, and ego control (e.g., the ability to monitor and regulate affect). Children in this study (N=249 maltreated and N=200 nonmaltreated) were assessed annually from age 6 to 10. Lastly, Proctor et al. (2010) concluded that a three-class model best characterized the internalizing symptoms. One group had consistently high levels of positive adjustment, a second alternated between positive adjustment and maladjustment, with decreasing levels of positive adjustment over time, and a third had high levels of initial maladjustment with moderate increases in adjustment beginning at age 10. Children in this study (N=279) were assessed bi-annually from age from 6 to 14. Although not always the case (Kim et al. 2009), more complex patterns of change/stability have been found among studies examining externalizing behaviors. Indeed, three studies (Proctor et al. 2010; Tabone et al. 2011; Thompson et al. 2011) drew subjects from the Longitudinal Study of Child Abuse and Neglect (LONGSCAN: Runyan et al. 1998). Two of these studies (Tabone et al. 2011; Thompson et al. 2011) concluded that a five-class model best fit the data. Slightly less heterogeneity (four classes) was found in a study using a subset of the LONGSCAN data composed of 279 maltreated children who had spent at least 5 months in out-of-home foster care) (Proctor et al. 2010).
Predictors of Group Membership and Trajectory Studies of the longitudinal impact of child maltreatment such as LONGSCAN (Runyan et al. 1998) are informed by ecological-developmental theory (Bronfenbrenner 1994) and social developmental theory (Catalano and Hawkins 1996). Ecological-developmental theory posits that children develop within a set of multiple, nested social systems. For example, the individual (personal characteristics) is nested within the microsystem (including family, school, and peers) which is nested within the broader exosystem (that includes neighbors, and family friends), which in turn is nested within a broader
J Abnorm Child Psychol
socio-cultural system. Social developmental theory places special emphasis on interactions with others and skills for interaction in predicting outcomes. These theories help inform research examining predictors of symptom trajectory. A number of characteristics of the individual are predictive of symptom trajectory class and/or growth factors. For example, sex, maltreatment type, age at time of event (Kim et al. 2009), internalizing symptoms, externalizing symptoms, ethnicity (Woodruff and Lee 2011), cognitive ability, and early social competence (Proctor et al. 2010) are each predictive of symptom trajectory. The presence of multiple risk factors (Tabone et al. 2011) or multiple forms of abuse (Kim et al. 2009) may confer additional risk. Characteristics of the child and the event are the most consistent predictors of trajectory class and/or growth. However, it should be noted that many of these variables have not been uniformly significant predictors across studies. For example, several studies did not find that sex was a significant predictor of trajectory (Kim et al. 2009; Nugent et al. 2009; Woodruff and Lee 2011). Additionally, several characteristics of the microsystem and the broader exosystem are predictive of symptom trajectory and/or growth factors. For example, within the microsystem caregiver alcohol use, caregiver depression (Tabone et al. 2011), and caregiver stability (Proctor et al. 2010) are predictive of symptom trajectory. Within the exosystem, community quality (Tabone et al. 2011) was a significant predictor.
Aims for the Current Paper One aim of this paper is to examine the number and shape of anxious/depressed symptom trajectories in a sample of children who were either abused or at elevated risk for abuse. Anxious/depressed symptoms were selected for two reasons. First, most GMM studies using child maltreatment victims have focused on broad-band symptom categories (often externalizing behaviors) with relatively less attention to more narrow-band internalizing symptoms. Second, both depression and anxiety are frequent down-stream consequences of child maltreatment (Gilbert et al. 2009). Thus, this is the first study to specifically examine the longitudinal trajectories of anxious/depressed symptoms in a sample of maltreated and atrisk children. A second aim of this paper is to examine potential predictors of trajectory class membership. Variables were selected that reflect the individual level and microsystem level and are thus theory informed. Individual level variables include sex, age at time of first Child Protective Service (CPS) report, severity of maltreatment history, and social competence (as indexed by peer popularity and peer aggression). Microsystem variables include number of visits by primary caregiver or family member to a health care provider for
problems related to the child (hereafter labeled number of PCP visits), satisfaction with the care received (hereafter labeled satisfaction with PCP visits), and amount of support received by primary maternal caregiver. With the exception of number of and satisfaction with PCP visits, these variables were chosen because prior work has demonstrated they are predictive of symptom trajectory and/or growth factors. Number of and satisfaction with PCP visits were included as frequency of adverse childhood experiences is predictive of need/receipt of medical care (Thompson et al. 2014).
Method Background and Study Design Data for the current study were drawn from the LONGSCAN Consortium of Studies of Child Abuse and Neglect (Runyan et al. 2011). The LONGSCAN Consortium was formed in 1990 and is composed of five data collection sites located in the East (EA), Midwest, (MW), South (SO), Southwest (SW) and Northwest (NW). The goal of this Consortium was to comprehensively assess children, their parents/caregivers, and teachers when the children were 4, 6, 8, 10, 12, 14, 16, 18, and 20 years old. The first interview following enrollment in the LONGSCAN study was scheduled to occur within 3 months of the child’s 4th birthday. Participants from the five sites differ in their risk status and severity of maltreatment. In addition, the five sites differ in methodology used to recruit subjects. Three of the sites (NW, MW, SO) recruited children based on referrals to Child Protective Services (CPS). The SW site recruited children who were removed from their families and placed into foster care during the first 42 months of life due to maltreatment. The EA site recruited children from primary health clinics who were at risk for maltreatment based on the presence of either child risk factors (e.g., low birth weight) or parental risk factors (e.g., drug use) though these children may not have a history of maltreatment. For the current study, children were included in the sample whether or not the maltreatment reports were substantiated because children reported to child welfare services are at risk of poor developmental outcomes regardless of substantiation status (Barth et al. 2008; Hussey, Chang, and Kotch 2006). For additional details on the design and methodology of the LONGSCAN Consortium see Runyan et al. (1998). Study Sample The study sample is comprised of 1354 children (48.5 % boys, n=657, 51.5 % girls, n=697). The majority of the sample was African American (53.2 %) followed by European American (26.1 %), mixed racial heritage (11.9 %), Hispanic (7.2 %),
J Abnorm Child Psychol
Native American (0.6 %), other (0.6 %), and Asian (0.3 %). The sample sizes at the five data collection sites were fairly similar (SW: 24.4 %, n =330; EA 20.8 %, n =282; NW: 18.8 %, n=254; MW: 18.1 %, n=245; and SO: 17.9 %, n= 243). Procedures Participants, their teachers, and caregivers completed a broad array of measures at ages 4, 6, 8, 10, 12, and 14 years. At these points, face-to-face interviews with the primary caregiver and the child were conducted. In the majority of sites, the primary caregiver was the biological mother (Range 73 % to 99 %) with the exception of the SW site, where the primary caregivers were more evenly divided among biological mother (31 %), foster mother (19 %), adoptive mother (16 %), grandmother (11 %), other female relative (9 %), non-relative (6 %), and male primary caregiver (8 %). Reporters could change over the course of the study. Beginning at age 6, information about the child’s academic performance and social adjustment were collected from the child’s teacher. Brief, annual telephone contacts were conducted with the caregivers, to enhance subject retention and assess service utilization, life events, and child behavior problems. Measures Symptom Outcome The CBCL/4–18 (Achenbach 1991) is a multi-scale empirically based instrument designed to assess a broad range of childhood psychopathology. This instrument was administered at ages 4, 6, 8, 10, 12, and 14. The CBCL/4– 18 includes scales assessing the following eight constructs: social withdrawal, somatic complaints, anxiety/depression, social problems, thought problems, attention problems, delinquent behavior and aggressive behavior. For the current study, only the anxiety/depression scale was used. For each item on the CBCL/4–18, the primary maternal caregiver was asked to rate her child’s behavior in the last 6 months on the following scale: 0=Not true to 2=very true or often true. Although raw scores on the CBCL can be converted to age-standardized scores, a minimum T score of 50 is assigned to scores that fall at midpoint percentiles of ≤50. Therefore, raw values were used as opposed to standardized scores as they provide greater variability. The CBCL/4–18 was normed on a sample of 2368 non-handicapped 4 to 18 year old children (Achenbach 1991). Values for internal consistency reliability (α) for the eight syndromes ranged from 0.62 to 0.92 for boys age 4–11 and from 0.66 to 0.92 for girls age 4–11. Maltreatment Status Investigators at the five sites reviewed CPS records to determine the presence and nature of maltreatment allegations among children in their samples. This review was done using the Modified Maltreatment Classification
System [MMCS: English & LONGSCAN Investigators, 1997; a LONGSCAN-modified version of the Barnett, Manly, and Cicchetti (1993) classification system]. Children were assigned a dichotomous code, based on presence/ absence of maltreatment allegations. For the current study, a composite index of maltreatment was developed in which the number of allegations of all forms of maltreatment was summed across all assessment points. The resultant value was used as a fixed, invariant index of maltreatment severity. In addition, the number of maltreatment allegations was computed at ages 4, 6, 8, 10, 12, and 14. This allowed for an examination of the dynamic relationship between maltreatment at each time point and symptoms of anxiety/depression. Individual Predictors The Teacher’s Estimation of Child’s Peer Status (TRPA) is a 7-item measure designed to assess how well the child is liked, the child’s social skills in relation to classmates, and how many peer nominations the child would receive in a given situation (e.g., number of nominations for most liked play/work partner). The first item asks teachers to rate how well the child is liked on a 5-point Likert-type scale anchored by 1=very well liked and 5=liked very little. Subsequent items are rated on a 5-point Likert-type scale with the following anchors: 1=one of the kids with the most nominations and 5=one of the kids with the fewest nominations. The TRPA yields an overall score and two subscales reflecting peer aggression (TRPA-Aggression) and peer (un) popularity (TRPA-Unpopularity). Items on the aggression scale were reverse scored. Thus, higher scores on both scales reflect more problematic peer relationships (i.e., high aggression, low popularity). In a sample of 3rd, 4th, and 5th grade children (Lemerise and Dodge 1990), total scores on the TRPA correlated positively with peer ratings (rs ranged from 0.55 to 0.65). Internal consistency reliability (α) for the full TRPA using the LONGSCAN data was 0.84 at age 6. In the current study, the subscales examining peer aggression and peer (un) popularity at age 6 were examined separately as possible predictors of trajectory class. In addition to the individual-level covariates listed above, the current study examined the impact on group membership of sex and age of child at first referral for any Child Protective Services event. Microsystem Predictors The Duke-UNC Functional Social Support Questionaire (FSSQ) (Broadhead, Gehlbach, DeGruy, and Kaplan 1988) is a 14-item measure designed to assess the caregiver’s perception of the amount and type of social support received. Items are rated on a 5-point Likerttype scale with the following anchors: 1=much less than I would like and 5=as much as I would like. LONGSCAN used a slightly modified version of the FSSQ, comprised of 10 items assessing confidant support, affective support, and instrumental support. Internal consistency reliability estimates (α) for the revised version of the FSSQ using the LONGSC
J Abnorm Child Psychol
AN data was 0.86 at age 6. In addition to social support, the current study examined the impact on group membership of two microsystem-level variables: number of PCP visits, and satisfaction with PCP visits. Data Analysis Latent Class Growth Analysis (LCGA) and GMM are analytical approaches that are used to identify trajectories of subgroups within a heterogeneous sample (B. Muthén and Muthén 2000). These analytic approaches differ in one important aspect. LCGA assumes no within-class variance on slope and intercept whereas GMM freely estimates these growth parameters. In both analyses, repeated measures of a continuous variable are used to identify classes with a categorical latent variable (C) that represents homogeneous subgroups within the sample (B. Muthén and Muthén 2000). Data analysis took place in several steps and closely follows the recommendations of Jung and Wickrama (2008). Initially the optimal number of classes was tested with within-class variance on growth factors constrained to zero (i.e., LCGA). The advantages to conducting this preliminary step include clear identification of classes (trajectories) and less computational burden (Jung and Wickrama 2008). Next the final optimal number of classes was tested with withinclass variance on growth parameters freely estimated (i.e., GMM). Lastly, tests of conditional models were conducted that assessed the likelihood of membership in a less pathological class relative to a more pathological class after controlling for the following time invariant (fixed) covariates: number of maltreatment allegations age 0–14, sex, age of child at first referral for any CPS event, peer aggression, peer (un) popularity, social support caregiver received, number of PCP visits, and satisfaction with PCP visits. The majority of these covariates were assessed at age six. Age six was chosen because it was as close as possible to the initial administration of the primary dependent variable and response rate was better at age six than age four. Because these covariates were assessed after the initial assessment of the dependent variable, they were used to predict class membership and slope, but not intercept. In addition, since number of maltreatment allegations was assessed biannually from age 4 to 14, this variable was examined as a time-varying covariate to examine the dynamic relationship between maltreatment and anxiety/ depression scale scores. This is consistent with recommendations from Proctor et al. (2010). Consistent with the recommendations of a number of authors, information gleaned from fit indices was combined with interpretability and value of information when making decisions on the number of classes to retain (Bauer and Curran 2003; B. Muthén 2003; Rindskopf 2003). The following fit indices were used: Bayesian Information Criterion (BIC; (Schwarz 1978), Akiake Information Criterion (AIC; Akaike
1970), the Adjusted Lo-Mendell-Rubin Likelihood Ratio Test (LRT; Lo, Mendell, and Rubin 2001), Bootstrap Likelihood Ratio Test (BLRT; McLachlan and Peel 2000), entropy, posterior probability estimates, clinical relevance and interpretability, and proportion of the sample within each class. The AIC and BIC are measures of the relative quality of a statistical model. Better fitting models have lower relative BIC and AIC values. Posterior probability refers to the likelihood that an individual child with a specific behavioral profile belongs to a specific trajectory group, and provides an objective basis for assessing the quality of the model fit. Entropy is a measure used for the separation of the latent classes which is based on the posterior class membership probabilities. Entropy measures how well one can predict class membership given the observed outcomes. Entropy values range from 0 to 1 with higher values representing better fit. The LRT and BLRT test the additive effect of the current model relative to the previous model with one less class and provide p values to indicate significance. Research suggests the BIC performed best among the information criteria indices but the BLRT was a consistent indicator of classes across all models considered (Nylund, Asparouhov, and Muthén 2007). Analyses were conducted using Mplus 5.1 (L. K. Muthén and Muthén 1998–2010). Regarding the primary dependent variable (anxiety/depression) data were present for 1220 (90.1 %), 1218 (90.0 %), 1124 (83.0 %), 1015 (75.0 %), 951 (70.2 %), and 930 (68.7 %) participants at ages 4, 6, 8, 10, 12, and 14 respectively. Little’s MCAR test was non-significant (χ2=179.42, DF=159, p=0.128) indicating that data were missing at random. Therefore, all individuals were included in unconditional model tests and missing data were addressed using Full Information Maximum Likelihood (FIML; Arbuckle 1996). However, A FIML approach to missing data was only employed with the anxious/depressed variables. Participants missing data on the covariates were excluded from tests of conditional models using listwise deletion, which is the default option in Mplus and is consistent with previous investigations (cf. Dickstein, Suvak, Litz, and Adler 2010).
Results Description of Sample There was considerable heterogeneity in frequency/severity of child maltreatment in this sample. The total number of child maltreatment allegations ranged from 0 to 56 (M=6.26, SD= 8.47). The mean age of first CPS referral was 2.47 years (SD= 3.40, n=9231). Data on peer aggression and peer (un) popularity at the age 6 assessment were available for approximately 1
Sample sizes are provided to reflect missingness on covariates.
J Abnorm Child Psychol
half of the sample (n=764 and n=766 respectively). Overall, the children in this sample were low to moderately aggressive (M=4.32, SD=2.51 possible range=2–10, high values indicate greater aggression) and moderately unpopular (M=9.25, SD=2.89; possible range=3–15, high values indicate greater unpopularity). At the age 6 assessment, approximately 27 % of the primary caregivers (n=369) reported a PCP visit for problems related to the child. The number of sessions ranged from 1 to 99 (M=15.96, SD=25.23) and respondents reported they were Bsomewhat^ satisfied with services received (M=1.53, SD= 0.84 Range=1–4). The vast majority of primary caregivers (n=1152) provided data on received social support at the age 6 assessments. Overall, these caregivers reported fairly high levels of social support (M=38.63, SD=9.10, Obtained Range 11 to 50, Possible range, 10 to 50).
Tests of Unconditional Latent Class Models Initially the adequacy of fit of a one-class latent growth model with both a linear and quadratic growth factor was tested. With the lone exception of the chi-square test, the remaining fit indices suggest that this is a well-fitting model, χ2 (12)= 51.24, p < 0.001, CFI = 0.98, TLI = 0.98, RMSEA = 0.05, SRMR=0.024. Next, LCGA models with two-five classes were tested which included both linear and quadratic growth factors. Across models 2–5 entropy values were acceptable with values ranging from 0.87 (five-class) to 0.89 (two-class). Values for the BIC decreased from the two-class model (32713) to the five-class model (32117) suggesting an improvement in model fit. Similarly, findings from the LMR and the BLRT indicated an improvement in model fit across the 2-, 3-, 4-, and 5-class models (change from −16986 to– 16027). However, the five-class model included one class with less than 1 % membership and the LMR value was non-significant, indicating that the five-class model did not provide a significantly better fit than the four-class model. When taken together, these results supported the four-class model. 12
Anxious-Depressed Scores
Fig. 1 Estimated means and posterior probabilities for 4-class growth mixture model with quadratic growth factor
A four-class GMM was estimated with linear and quadratic growth shapes estimated in each class. However, the latent variable covariance matrix was not positive definite. Examination of the assessment diagnostics revealed negative estimated variance terms for growth parameters on class one. Fixing the variance in growth terms in class one to zero resulted in a successful model run (Wang and Wang 2012). This model is illustrated graphically in Fig. 1 and parameter estimates are provided in Table 1. For the first latent class (n= 631), the linear form fit well and the latent means of intercept (μI =0.88, p
Symptom Trajectories Among Child Survivors of Maltreatment: Findings from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN) Dean Lauterbach & Cherie Armour
# Springer Science+Business Media New York 2015
Abstract Very few studies have investigated the longitudinal trajectory of depression and anxiety related symptomatology among child victims of maltreatment or among those at risk for maltreatment. The current study examined latent class trajectories of anxiety/depression symptoms in a sample of 1354 (n=657 boys, n=697 girls) victimized or at risk children using data collected from the Longtitudinal Studies of Child Abuse and Neglect (LONGSCAN). Four trajectory groups were identified labeled low-stable, moderate-stable, moderate-increasing, and high-decreasing. This study also sought to investigate predictors of group membership. Relative to the lowstable group, membership in the three more pathological groups (i.e., moderate-stable, moderate-increasing, and highThe data used in this publication were made available by the National Data Archive on Child Abuse and Neglect, Cornell University, Ithaca, NY, and have been used with permission. Data from Longitudinal Studies of Child Abuse and Neglect (LONGSCAN) Assessments 0–14 were originally collected by Desmond K. Runyan, Howard Dubowitz, Diana J. English, Jonathan Kotch, Alan Litrownik, Richard Thompson and Terri Lewis & The LONGSCAN Investigator Group. Funding for the project was provided by the Office on Child Abuse and Neglect (OCAN), Children’s Bureau, Administration for Children and Families, Dept. of Health and Human Services (The National Center on Child Abuse and Neglect (NCCAN), under the Office of Human Services funded this consortium of studies during the early years of data collection from 04/ 01/1991 until NCCAN became part of OCAN in 1998.) The collector of the original data, the funder, NDACAN, Cornell University and their agents or employees bear no responsibility for the analysis or interpretations. D. Lauterbach (*) Department of Psychology, Eastern Michigan University, 303a Mark Jefferson Science Hall, Ypsilanti, MI 48197, USA e-mail: [email protected] C. Armour School of Psychology, University of Ulster at Coleraine Campus, Coleraine, Northern Ireland, UK
decreasing) was predicted by a greater number of maltreatment allegations, more visits to a primary care physician for psychological issues, less perceived support by primary maternal caregiver, and lower rated popularity of the child. Implications for early identification of child maltreatment victims in primary health care settings was discussed. Keywords Child maltreatment . Longitudinal . Growth mixture modeling
The experience of childhood physical, sexual, or emotional abuse has significant long term consequences. These consequences were summarized by Gilbert et al. (2009), who note that 25 % to 30 % of maltreated children meet criteria for major depression by their late 20s and 17 % to 23 % of maltreated children meet criteria for PTSD in their late 20s. However, in a controversial meta analysis (Rind, Tromovitch, and Bauserman 1998) it was concluded that child sexual abuse victims are best characterized as being only Bslightly less well-adjusted than controls^ long term (Rind et al. 1998, p. 22). While a critical examination of this meta-analysis called into question some of the study’s conclusions (cf. Dallam, Gleaves, Cepeda-Benito, Silberg, and Kraemer 2001) it is readily apparent that the longitudinal course of psychopathological symptoms among child maltreatment victims is an area of considerable interest. The substantial differences in findings suggests variability in symptom trajectories that is obscured using traditional analytic techniques. Conventional approaches to modeling the longitudinal course of symptoms assume that individuals are sampled from a single population and that a single growth trajectory will adequately describe the entire population. However, anecdotal clinical observations and empirical
J Abnorm Child Psychol
research suggest the presence of subgroups characterized by differences in change over time. Growth mixture modeling (GMM) is a person-centered statistical technique that allows for the identification of homogenous groups (classes) of children based on symptom trajectory (B. Muthén 2004; Nagin 2005). Therefore, it is possible to identify latent classes of maltreated children whose symptoms display differential trajectories over time. In addition, it is possible to examine potential predictors of group membership and thus trajectory. This stands in contrast to variable-centered approaches that describe covariation among variables. Person-centered approaches are better suited to addressing individual differences in patterns of change over time (Laursen and Hoff 2006). Therefore, this paper will utilize GMM to examine the number, shape, and predictors of anxious/depressed symptom trajectories in a sample of children who were either abused or at elevated risk for abuse. The literature review that follows will discuss studies in the trauma field that have utilized GMM in examining the psychopathological symptom trajectories of child maltreatment victims and potential predictors of trajectory classes. Special attention will be devoted to studies examining internalizing symptom trajectories.
Symptom Trajectories Among Child Maltreatment Victims Several recent studies have examined the heterogeneity of symptom change among child (Kim, Cicchetti, Rogosch, and Manly 2009; Proctor, Skriner, Roesch, and Litrownik 2010; Tabone et al. 2011; Woodruff and Lee 2011) and child/adolescent (Nugent et al. 2009; Thompson et al. 2011) maltreatment victims. In the majority of studies, either the Externalizing or the Internalizing broad-band scale of the Child Behavior Checklist (CBCL: Achenbach 1991) was one of the dependent variables. The lone exception was Nugent et al. (2009) which assessed PTSD symptomatology. Findings from these studies differ markedly in the number of trajectories that best characterize the sample. Three studies of child and child/adolescent victims of maltreatment identified relatively little heterogeneity in symptom change over time with the number of classes ranging from one to three. Subjects in these studies have included children/ adolescents who were referred to the U.S. Navy’s Family Advocacy Program because of allegations of child sexual abuse, child physical abuse, or intimate partner violence (Nugent et al. 2009), maltreated children who had attended a summer day camp research program (Kim et al. 2009), and maltreated children who had spent at least 5 months in out-ofhome foster care (Proctor et al. 2010). Nugent et al. (2009) concluded that a linear two-class model provided the best fit to the data. One class was characterized by minimal symptoms across assessment frames with a slight increase over time
whereas the second class was characterized by moderately high symptoms at initial assessment which were relatively stable over time. Children in this study (N=201) ranged in age from 7 to 18 and were followed for 40 months. Kim et al. (2009) concluded that a two-class solution best characterized the personality characteristic ego resiliency among maltreated children. Ego resiliency refers to the ability to flexibly use problem solving strategies that are well suited to changing circumstances (Block and Block 1980) and high ego resiliency is predictive of low internalizing symptoms (Cicchetti and Rogosch 1997). One group had increasing levels of ego resiliency between ages 7 and 10 and the second had consistently decreasing levels of this characteristic. This same study found that a one-class solution best characterized externalizing symptoms, internalizing symptoms, and ego control (e.g., the ability to monitor and regulate affect). Children in this study (N=249 maltreated and N=200 nonmaltreated) were assessed annually from age 6 to 10. Lastly, Proctor et al. (2010) concluded that a three-class model best characterized the internalizing symptoms. One group had consistently high levels of positive adjustment, a second alternated between positive adjustment and maladjustment, with decreasing levels of positive adjustment over time, and a third had high levels of initial maladjustment with moderate increases in adjustment beginning at age 10. Children in this study (N=279) were assessed bi-annually from age from 6 to 14. Although not always the case (Kim et al. 2009), more complex patterns of change/stability have been found among studies examining externalizing behaviors. Indeed, three studies (Proctor et al. 2010; Tabone et al. 2011; Thompson et al. 2011) drew subjects from the Longitudinal Study of Child Abuse and Neglect (LONGSCAN: Runyan et al. 1998). Two of these studies (Tabone et al. 2011; Thompson et al. 2011) concluded that a five-class model best fit the data. Slightly less heterogeneity (four classes) was found in a study using a subset of the LONGSCAN data composed of 279 maltreated children who had spent at least 5 months in out-of-home foster care) (Proctor et al. 2010).
Predictors of Group Membership and Trajectory Studies of the longitudinal impact of child maltreatment such as LONGSCAN (Runyan et al. 1998) are informed by ecological-developmental theory (Bronfenbrenner 1994) and social developmental theory (Catalano and Hawkins 1996). Ecological-developmental theory posits that children develop within a set of multiple, nested social systems. For example, the individual (personal characteristics) is nested within the microsystem (including family, school, and peers) which is nested within the broader exosystem (that includes neighbors, and family friends), which in turn is nested within a broader
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socio-cultural system. Social developmental theory places special emphasis on interactions with others and skills for interaction in predicting outcomes. These theories help inform research examining predictors of symptom trajectory. A number of characteristics of the individual are predictive of symptom trajectory class and/or growth factors. For example, sex, maltreatment type, age at time of event (Kim et al. 2009), internalizing symptoms, externalizing symptoms, ethnicity (Woodruff and Lee 2011), cognitive ability, and early social competence (Proctor et al. 2010) are each predictive of symptom trajectory. The presence of multiple risk factors (Tabone et al. 2011) or multiple forms of abuse (Kim et al. 2009) may confer additional risk. Characteristics of the child and the event are the most consistent predictors of trajectory class and/or growth. However, it should be noted that many of these variables have not been uniformly significant predictors across studies. For example, several studies did not find that sex was a significant predictor of trajectory (Kim et al. 2009; Nugent et al. 2009; Woodruff and Lee 2011). Additionally, several characteristics of the microsystem and the broader exosystem are predictive of symptom trajectory and/or growth factors. For example, within the microsystem caregiver alcohol use, caregiver depression (Tabone et al. 2011), and caregiver stability (Proctor et al. 2010) are predictive of symptom trajectory. Within the exosystem, community quality (Tabone et al. 2011) was a significant predictor.
Aims for the Current Paper One aim of this paper is to examine the number and shape of anxious/depressed symptom trajectories in a sample of children who were either abused or at elevated risk for abuse. Anxious/depressed symptoms were selected for two reasons. First, most GMM studies using child maltreatment victims have focused on broad-band symptom categories (often externalizing behaviors) with relatively less attention to more narrow-band internalizing symptoms. Second, both depression and anxiety are frequent down-stream consequences of child maltreatment (Gilbert et al. 2009). Thus, this is the first study to specifically examine the longitudinal trajectories of anxious/depressed symptoms in a sample of maltreated and atrisk children. A second aim of this paper is to examine potential predictors of trajectory class membership. Variables were selected that reflect the individual level and microsystem level and are thus theory informed. Individual level variables include sex, age at time of first Child Protective Service (CPS) report, severity of maltreatment history, and social competence (as indexed by peer popularity and peer aggression). Microsystem variables include number of visits by primary caregiver or family member to a health care provider for
problems related to the child (hereafter labeled number of PCP visits), satisfaction with the care received (hereafter labeled satisfaction with PCP visits), and amount of support received by primary maternal caregiver. With the exception of number of and satisfaction with PCP visits, these variables were chosen because prior work has demonstrated they are predictive of symptom trajectory and/or growth factors. Number of and satisfaction with PCP visits were included as frequency of adverse childhood experiences is predictive of need/receipt of medical care (Thompson et al. 2014).
Method Background and Study Design Data for the current study were drawn from the LONGSCAN Consortium of Studies of Child Abuse and Neglect (Runyan et al. 2011). The LONGSCAN Consortium was formed in 1990 and is composed of five data collection sites located in the East (EA), Midwest, (MW), South (SO), Southwest (SW) and Northwest (NW). The goal of this Consortium was to comprehensively assess children, their parents/caregivers, and teachers when the children were 4, 6, 8, 10, 12, 14, 16, 18, and 20 years old. The first interview following enrollment in the LONGSCAN study was scheduled to occur within 3 months of the child’s 4th birthday. Participants from the five sites differ in their risk status and severity of maltreatment. In addition, the five sites differ in methodology used to recruit subjects. Three of the sites (NW, MW, SO) recruited children based on referrals to Child Protective Services (CPS). The SW site recruited children who were removed from their families and placed into foster care during the first 42 months of life due to maltreatment. The EA site recruited children from primary health clinics who were at risk for maltreatment based on the presence of either child risk factors (e.g., low birth weight) or parental risk factors (e.g., drug use) though these children may not have a history of maltreatment. For the current study, children were included in the sample whether or not the maltreatment reports were substantiated because children reported to child welfare services are at risk of poor developmental outcomes regardless of substantiation status (Barth et al. 2008; Hussey, Chang, and Kotch 2006). For additional details on the design and methodology of the LONGSCAN Consortium see Runyan et al. (1998). Study Sample The study sample is comprised of 1354 children (48.5 % boys, n=657, 51.5 % girls, n=697). The majority of the sample was African American (53.2 %) followed by European American (26.1 %), mixed racial heritage (11.9 %), Hispanic (7.2 %),
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Native American (0.6 %), other (0.6 %), and Asian (0.3 %). The sample sizes at the five data collection sites were fairly similar (SW: 24.4 %, n =330; EA 20.8 %, n =282; NW: 18.8 %, n=254; MW: 18.1 %, n=245; and SO: 17.9 %, n= 243). Procedures Participants, their teachers, and caregivers completed a broad array of measures at ages 4, 6, 8, 10, 12, and 14 years. At these points, face-to-face interviews with the primary caregiver and the child were conducted. In the majority of sites, the primary caregiver was the biological mother (Range 73 % to 99 %) with the exception of the SW site, where the primary caregivers were more evenly divided among biological mother (31 %), foster mother (19 %), adoptive mother (16 %), grandmother (11 %), other female relative (9 %), non-relative (6 %), and male primary caregiver (8 %). Reporters could change over the course of the study. Beginning at age 6, information about the child’s academic performance and social adjustment were collected from the child’s teacher. Brief, annual telephone contacts were conducted with the caregivers, to enhance subject retention and assess service utilization, life events, and child behavior problems. Measures Symptom Outcome The CBCL/4–18 (Achenbach 1991) is a multi-scale empirically based instrument designed to assess a broad range of childhood psychopathology. This instrument was administered at ages 4, 6, 8, 10, 12, and 14. The CBCL/4– 18 includes scales assessing the following eight constructs: social withdrawal, somatic complaints, anxiety/depression, social problems, thought problems, attention problems, delinquent behavior and aggressive behavior. For the current study, only the anxiety/depression scale was used. For each item on the CBCL/4–18, the primary maternal caregiver was asked to rate her child’s behavior in the last 6 months on the following scale: 0=Not true to 2=very true or often true. Although raw scores on the CBCL can be converted to age-standardized scores, a minimum T score of 50 is assigned to scores that fall at midpoint percentiles of ≤50. Therefore, raw values were used as opposed to standardized scores as they provide greater variability. The CBCL/4–18 was normed on a sample of 2368 non-handicapped 4 to 18 year old children (Achenbach 1991). Values for internal consistency reliability (α) for the eight syndromes ranged from 0.62 to 0.92 for boys age 4–11 and from 0.66 to 0.92 for girls age 4–11. Maltreatment Status Investigators at the five sites reviewed CPS records to determine the presence and nature of maltreatment allegations among children in their samples. This review was done using the Modified Maltreatment Classification
System [MMCS: English & LONGSCAN Investigators, 1997; a LONGSCAN-modified version of the Barnett, Manly, and Cicchetti (1993) classification system]. Children were assigned a dichotomous code, based on presence/ absence of maltreatment allegations. For the current study, a composite index of maltreatment was developed in which the number of allegations of all forms of maltreatment was summed across all assessment points. The resultant value was used as a fixed, invariant index of maltreatment severity. In addition, the number of maltreatment allegations was computed at ages 4, 6, 8, 10, 12, and 14. This allowed for an examination of the dynamic relationship between maltreatment at each time point and symptoms of anxiety/depression. Individual Predictors The Teacher’s Estimation of Child’s Peer Status (TRPA) is a 7-item measure designed to assess how well the child is liked, the child’s social skills in relation to classmates, and how many peer nominations the child would receive in a given situation (e.g., number of nominations for most liked play/work partner). The first item asks teachers to rate how well the child is liked on a 5-point Likert-type scale anchored by 1=very well liked and 5=liked very little. Subsequent items are rated on a 5-point Likert-type scale with the following anchors: 1=one of the kids with the most nominations and 5=one of the kids with the fewest nominations. The TRPA yields an overall score and two subscales reflecting peer aggression (TRPA-Aggression) and peer (un) popularity (TRPA-Unpopularity). Items on the aggression scale were reverse scored. Thus, higher scores on both scales reflect more problematic peer relationships (i.e., high aggression, low popularity). In a sample of 3rd, 4th, and 5th grade children (Lemerise and Dodge 1990), total scores on the TRPA correlated positively with peer ratings (rs ranged from 0.55 to 0.65). Internal consistency reliability (α) for the full TRPA using the LONGSCAN data was 0.84 at age 6. In the current study, the subscales examining peer aggression and peer (un) popularity at age 6 were examined separately as possible predictors of trajectory class. In addition to the individual-level covariates listed above, the current study examined the impact on group membership of sex and age of child at first referral for any Child Protective Services event. Microsystem Predictors The Duke-UNC Functional Social Support Questionaire (FSSQ) (Broadhead, Gehlbach, DeGruy, and Kaplan 1988) is a 14-item measure designed to assess the caregiver’s perception of the amount and type of social support received. Items are rated on a 5-point Likerttype scale with the following anchors: 1=much less than I would like and 5=as much as I would like. LONGSCAN used a slightly modified version of the FSSQ, comprised of 10 items assessing confidant support, affective support, and instrumental support. Internal consistency reliability estimates (α) for the revised version of the FSSQ using the LONGSC
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AN data was 0.86 at age 6. In addition to social support, the current study examined the impact on group membership of two microsystem-level variables: number of PCP visits, and satisfaction with PCP visits. Data Analysis Latent Class Growth Analysis (LCGA) and GMM are analytical approaches that are used to identify trajectories of subgroups within a heterogeneous sample (B. Muthén and Muthén 2000). These analytic approaches differ in one important aspect. LCGA assumes no within-class variance on slope and intercept whereas GMM freely estimates these growth parameters. In both analyses, repeated measures of a continuous variable are used to identify classes with a categorical latent variable (C) that represents homogeneous subgroups within the sample (B. Muthén and Muthén 2000). Data analysis took place in several steps and closely follows the recommendations of Jung and Wickrama (2008). Initially the optimal number of classes was tested with within-class variance on growth factors constrained to zero (i.e., LCGA). The advantages to conducting this preliminary step include clear identification of classes (trajectories) and less computational burden (Jung and Wickrama 2008). Next the final optimal number of classes was tested with withinclass variance on growth parameters freely estimated (i.e., GMM). Lastly, tests of conditional models were conducted that assessed the likelihood of membership in a less pathological class relative to a more pathological class after controlling for the following time invariant (fixed) covariates: number of maltreatment allegations age 0–14, sex, age of child at first referral for any CPS event, peer aggression, peer (un) popularity, social support caregiver received, number of PCP visits, and satisfaction with PCP visits. The majority of these covariates were assessed at age six. Age six was chosen because it was as close as possible to the initial administration of the primary dependent variable and response rate was better at age six than age four. Because these covariates were assessed after the initial assessment of the dependent variable, they were used to predict class membership and slope, but not intercept. In addition, since number of maltreatment allegations was assessed biannually from age 4 to 14, this variable was examined as a time-varying covariate to examine the dynamic relationship between maltreatment and anxiety/ depression scale scores. This is consistent with recommendations from Proctor et al. (2010). Consistent with the recommendations of a number of authors, information gleaned from fit indices was combined with interpretability and value of information when making decisions on the number of classes to retain (Bauer and Curran 2003; B. Muthén 2003; Rindskopf 2003). The following fit indices were used: Bayesian Information Criterion (BIC; (Schwarz 1978), Akiake Information Criterion (AIC; Akaike
1970), the Adjusted Lo-Mendell-Rubin Likelihood Ratio Test (LRT; Lo, Mendell, and Rubin 2001), Bootstrap Likelihood Ratio Test (BLRT; McLachlan and Peel 2000), entropy, posterior probability estimates, clinical relevance and interpretability, and proportion of the sample within each class. The AIC and BIC are measures of the relative quality of a statistical model. Better fitting models have lower relative BIC and AIC values. Posterior probability refers to the likelihood that an individual child with a specific behavioral profile belongs to a specific trajectory group, and provides an objective basis for assessing the quality of the model fit. Entropy is a measure used for the separation of the latent classes which is based on the posterior class membership probabilities. Entropy measures how well one can predict class membership given the observed outcomes. Entropy values range from 0 to 1 with higher values representing better fit. The LRT and BLRT test the additive effect of the current model relative to the previous model with one less class and provide p values to indicate significance. Research suggests the BIC performed best among the information criteria indices but the BLRT was a consistent indicator of classes across all models considered (Nylund, Asparouhov, and Muthén 2007). Analyses were conducted using Mplus 5.1 (L. K. Muthén and Muthén 1998–2010). Regarding the primary dependent variable (anxiety/depression) data were present for 1220 (90.1 %), 1218 (90.0 %), 1124 (83.0 %), 1015 (75.0 %), 951 (70.2 %), and 930 (68.7 %) participants at ages 4, 6, 8, 10, 12, and 14 respectively. Little’s MCAR test was non-significant (χ2=179.42, DF=159, p=0.128) indicating that data were missing at random. Therefore, all individuals were included in unconditional model tests and missing data were addressed using Full Information Maximum Likelihood (FIML; Arbuckle 1996). However, A FIML approach to missing data was only employed with the anxious/depressed variables. Participants missing data on the covariates were excluded from tests of conditional models using listwise deletion, which is the default option in Mplus and is consistent with previous investigations (cf. Dickstein, Suvak, Litz, and Adler 2010).
Results Description of Sample There was considerable heterogeneity in frequency/severity of child maltreatment in this sample. The total number of child maltreatment allegations ranged from 0 to 56 (M=6.26, SD= 8.47). The mean age of first CPS referral was 2.47 years (SD= 3.40, n=9231). Data on peer aggression and peer (un) popularity at the age 6 assessment were available for approximately 1
Sample sizes are provided to reflect missingness on covariates.
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half of the sample (n=764 and n=766 respectively). Overall, the children in this sample were low to moderately aggressive (M=4.32, SD=2.51 possible range=2–10, high values indicate greater aggression) and moderately unpopular (M=9.25, SD=2.89; possible range=3–15, high values indicate greater unpopularity). At the age 6 assessment, approximately 27 % of the primary caregivers (n=369) reported a PCP visit for problems related to the child. The number of sessions ranged from 1 to 99 (M=15.96, SD=25.23) and respondents reported they were Bsomewhat^ satisfied with services received (M=1.53, SD= 0.84 Range=1–4). The vast majority of primary caregivers (n=1152) provided data on received social support at the age 6 assessments. Overall, these caregivers reported fairly high levels of social support (M=38.63, SD=9.10, Obtained Range 11 to 50, Possible range, 10 to 50).
Tests of Unconditional Latent Class Models Initially the adequacy of fit of a one-class latent growth model with both a linear and quadratic growth factor was tested. With the lone exception of the chi-square test, the remaining fit indices suggest that this is a well-fitting model, χ2 (12)= 51.24, p < 0.001, CFI = 0.98, TLI = 0.98, RMSEA = 0.05, SRMR=0.024. Next, LCGA models with two-five classes were tested which included both linear and quadratic growth factors. Across models 2–5 entropy values were acceptable with values ranging from 0.87 (five-class) to 0.89 (two-class). Values for the BIC decreased from the two-class model (32713) to the five-class model (32117) suggesting an improvement in model fit. Similarly, findings from the LMR and the BLRT indicated an improvement in model fit across the 2-, 3-, 4-, and 5-class models (change from −16986 to– 16027). However, the five-class model included one class with less than 1 % membership and the LMR value was non-significant, indicating that the five-class model did not provide a significantly better fit than the four-class model. When taken together, these results supported the four-class model. 12
Anxious-Depressed Scores
Fig. 1 Estimated means and posterior probabilities for 4-class growth mixture model with quadratic growth factor
A four-class GMM was estimated with linear and quadratic growth shapes estimated in each class. However, the latent variable covariance matrix was not positive definite. Examination of the assessment diagnostics revealed negative estimated variance terms for growth parameters on class one. Fixing the variance in growth terms in class one to zero resulted in a successful model run (Wang and Wang 2012). This model is illustrated graphically in Fig. 1 and parameter estimates are provided in Table 1. For the first latent class (n= 631), the linear form fit well and the latent means of intercept (μI =0.88, p
