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Risk and Protective Factors for Treatment Dropout in a Child Maltreatment Population

Abstract

Many children start but do not complete trauma treatment, and there is little knowledge of factors that predict treatment dropout in children who have endured maltreatment. The current study examines the risk and protective factors associated with premature treatment dropout within a sample of 118 children (aged 3–18) referred to a Child Advocacy Centre due to maltreatment, specifically abuse and neglect. In this retrospective chart review, data on risk (i.e., adverse childhood experiences [ACEs] and number of presenting clinical symptoms at intake) and protective factors (e.g., peer support, caregiver support) were extracted from clinical files by two trained coders using a standardized data extraction protocol. Results revealed that, after adjusting for child age, ACEs score, and presenting clinical concerns, children with more protective factors were less likely to drop out of treatment (OR=0.40, 95% CI [0.24, 0.69]). Child age also emerged as a significant predictor of treatment dropout, such that older children were more likely to drop out of treatment prematurely (OR=1.16, 95% CI [1.01, 1.32]). Results suggest that older children and children with fewer protective factors present may benefit from increased retention efforts to reduce treatment dropout.

Introduction

Child maltreatment, which includes physical, sexual, and emotional abuse, neglect, and exposure to domestic violence, is a prominent public health concern with approximately 12% of US children experiencing substantiated maltreatment (Wildeman et al., 2014). With an immense economic impact (Bellis et al., 2019; Gelles & Perlman, 2012) and potentially lasting individual consequences for physical and mental wellbeing (Heim, Shugart, Craighead, & Nemeroff, 2010; MacMillan et al., 2001), treatments that mitigate adverse effects and prevent future victimization are essential. While a variety of trauma-focused treatments exist with promising outcomes (Chaffin & Friedrich, 2004; Lenz & Hollenbaugh, 2015; Morina, Koerssen, & Pollet, 2016), a high proportion of children that have access to these treatments drop out or intermittently attend treatment sessions. Specifically, studies with children who have experienced maltreatment report dropout rates from trauma-focused treatments ranging from 25 to 69% (Cohen & Mannarino, 2000; Cohen, Mannarino, & Iyengar, 2011; Wamser-Nanney & Steinzor, 2016). Taken together, understanding the factors that lead to and mitigate potential treatment dropout is critical for informing the implementation of trauma-based treatment for maltreated children.

Engaging children and their families in any treatment can be a significant challenge, and those affected by trauma face unique barriers to treatment such as parental guilt, avoidance of discussing trauma, or underestimating current functioning after experiencing trauma (Gopalan et al., 2010). Children who do not attend, participate, or drop out prematurely from treatment are at risk for post-traumatic stress disorder (PTSD), depression, substance misuse, and functional impairment at home and school (Angold, Costello, Burns, Erkanli, & Farmer, 2000; Cohen, Mannarino, & Deblinger, 2017; Hetzel-Riggin, Brausch, & Montgomery, 2007). In order to mitigate the potential negative mental health outcomes of maltreatment, it is crucial to identify the individual child (e.g., age, presenting clinical symptoms), caregiver, and environmental (i.e., school, family, and friend) factors that help children and their families attend and complete treatment. Accordingly, the current study employs a retrospective chart review of 118 children referred to a Child Advocacy Centre due to maltreatment to examine how risk and protective factors are associated with treatment dropout. Identifying these factors may have important implications for treatment targets and help guide clinicians’ decisions for children who have been maltreated.

Risk Factors for Treatment Dropout

Developmental psychopathology theory suggests that there are multiple factors that may contribute to either maladaptive or successful adaptation following the experience of maltreatment in childhood (Bronfenbrenner, 1992; Cicchetti & Cohen, 1995). Consistent with this notion, treatment completion and dropout can also be influenced by various ecological factors, including those within the child’s immediate environment (e.g., social, emotional, and financial resources) and the therapeutic context. A meta-analysis by de Haan, Boon, de Jong, Hoeve, and Vermeiren (2013) found that lower child IQ, comorbid mental health diagnoses, low social functioning, family socioeconomic status (SES), negative life events, and poor parenting were all risk factors for dropout in families accessing general mental health treatment. Child age has also been found to be associated with treatment dropout in a number of studies using child maltreatment samples, with older children in particular being at risk of premature dropout (Celano, NeMoyer, Stagg, & Scott, 2018; Fraynt et al., 2014; Wamser-Nanney & Steinzor, 2016). However, this finding has not been consistent across the literature, with some studies finding no effect of child age on treatment dropout (Koverola, Murtaugh, Connors, Reeves, & Papas, 2007; Sprang et al., 2013).

There is evidence to suggest that adversity and maltreatment experiences cluster together—those who have been exposed to one type of trauma are at risk for experiencing another (Finkelhor, Ormrod, & Turner, 2007). Moreover, the accumulation of multiple adverse childhood experiences (ACEs) is associated with increased risk for poor mental health, behavioral, and physical health outcomes, including substance misuse, suicide, delinquency, obesity, and diabetes (Anda et al., 2006; Dube et al., 2001; Ford, Elhai, Connor, & Frueh, 2010; Williamson, Thompson, Anda, Dietz, & Felitti, 2002). Children who present with a greater number of ACEs are more likely to have increased trauma or behavioral symptoms than those with single-event or single types of ACEs (Cloitre et al., 2009). However, there remains a research gap in how ACEs and presenting clinical symptoms contribute to treatment dropout in a clinical sample of children who have been maltreated.

Protective Factors for Treatment Dropout

Despite the vulnerability of children who have been maltreated, multiple factors at the individual, family, and community level also serve as protective factors that may preclude significant impairment, including supportive relationships and stable home environments (Afifi & Macmillan, 2011). Conceptually different from risk, protective factors broadly refer to influences that may promote resilience and mitigate impairment in the face of considerable adversity (Afifi & Macmillan, 2011; Masten, 2018). Protective factors encompass a range of intrinsic and extrinsic resources that an individual can pull from in times of adversity and that may support engagement in treatment. Although the accumulation of adversity experiences may play a role in children’s treatment outcomes, protective factors may reduce trauma-related distress (Racine, Eirich, Dimitropoulos, Hartwick, & Madigan, 2020), which subsequently has the potential to reduce the risk for treatment dropout. Children with more protective factors may be able to draw from and build upon these factors to stay engaged in treatment and complete required components; however, those with few protective factors may lack the familial or environmental support to continue to attend treatment.

Although numerous studies have been conducted on risk factors for treatment dropout in child psychotherapy broadly (de Haan et al., 2013), very few investigations to date have examined protective factors that mitigate the risk for treatment dropout in children engaged in trauma treatment specifically. Cohen and Mannarino (1998) demonstrated that parent emotional support positively impacts treatment outcomes in children who have been sexually abused. Furthermore, Sharma-Patel and Brown (2016) reported that child emotional regulation improved trajectories of PTSD treatment outcomes, and Kisiel, Summersett-Ringgold, Weil, and McClelland (2017) found that protective factors such as coping skills and community support reduced mental health symptoms and risk behaviors among children and youth in a child welfare system. These findings suggest that protective factors may also help children and their families stay engaged in, and committed to, the treatment process and, therefore, preclude children from the poor outcome of treatment dropout. Elucidating whether the accumulation of protective factors is associated with treatment dropout could inform service delivery by pointing to protective strengths that could be harnessed and enriched in treatment to retain vulnerable families and promote favorable treatment outcomes.

Present Study

Risk and protective factors have historically been discussed in relation to the development and course of maladaptation in children (Rolf, Masten, Cicchetti, Nuechterlein, & Weintraub, 1990) and thus serve as a useful framework for understanding the various factors that may contribute to treatment dropout following exposure to child maltreatment. Up to 69% of children who are referred for child trauma treatment dropout prematurely and do not receive the support and services they need (Cohen et al., 2011; Cohen & Mannarino, 2000; Wamser-Nanney & Steinzor, 2016). However, the provision of intervention following child maltreatment has been shown to reduce trauma symptoms and poor outcomes for children (Cohen, Mannarino, & Knudsen, 2005; Scheeringa, Weems, Cohen, Amaya-Jackson, & Guthrie, 2011; Thomas & Zimmer-Gembeck, 2012). Although high rates of dropout are seen in child maltreatment populations, there is currently a dearth of research to disentangle the risk and protective factors contributing to this dropout in clinical samples. Therefore, the overarching goal of the present study was to identify risk factors for treatment dropout, as well as protective factors that preclude treatment dropout.

Specifically, we set out to examine whether ACEs and the number of clinical symptoms children present with at intake predict treatment dropout and whether the accumulation of individual child (i.e., personal skills, peer support, and social skills), caregiver (i.e., physical and psychological caregiving), and contextual protective factors (i.e., spiritual, educational, and cultural support) protect against treatment dropout. In line with previous research that demonstrated that those with 4 or more ACEs are at an increased risk for poor outcomes (Dube et al., 2003), it was hypothesized that children with more ACEs would be more likely to drop out of treatment than those with fewer ACEs. Consistent with findings from Eslinger, Sprang, and Otis (2014), it was also hypothesized that children with more presenting clinical concerns would be more likely to drop out of treatment. Finally, based on findings that suggest that protective factors can offset poor outcomes for maltreated children (Kisiel et al., 2017), it was hypothesized that children with more protective factors would be less likely to drop out of treatment.

Method

A retrospective chart review of 176 children between 3 and 18 years old referred to a Child Advocacy Centre in an urban area (removed to retain anonymity) was conducted. This maltreatment service provides treatment on an outpatient basis using evidence-based practice to assess and treat complex and severe child maltreatment cases. All assessment and treatment are provided by registered psychologists or social workers with a minimum of a master’s degree. All intake information is collected by one of three intake workers who follow a semi-structured intake interview that is completed on the phone with the referral source. Intake workers receive standardized training on the interview protocol and can receive additional guidance from the clinical team lead (master’s-level social worker) as needed. Files reviewed were open between the dates of January 2016 and June 2017, and the case file review occurred between March 2017 and October 2018. To be eligible for the current study, files had to be opened after a designated date of January 2016, have available data for child treatment outcome (i.e., completion or dropout), and the child could no longer be receiving active treatment (i.e., the case file was considered closed). Children who were referred for treatment elsewhere (n = 44) or who were not deemed appropriate for treatment (n = 14) were not included in analyses. Those who were considered inappropriate for treatment were deemed so due to the child’s refusal to discuss or acknowledge abuse (n = 2), family refusal to engage in treatment or hindering treatment (e.g., keeping secrets from child; n = 4), and family instability (n = 8). These children were not included because it was possible that those who were referred elsewhere or for whom treatment was deemed inappropriate at the time of referral completed treatment elsewhere or at a later time. Therefore, of the families referred to the agency, 118 were retained for analyses (see Fig. 1 for a flow chart). Ethics approval for the current study was obtained from the institutional review board and a waiver of consent for retrospective file review was obtained.

Fig. 1
figure1

Flow chart of case files included in the current study and treatment outcomes

Descriptive statistics for the sample are presented in Table 1. In brief, the age of children receiving services ranged from 3.92–17.67 (M = 10.48, SD = 3.49) and most (65%) were female. Due to few files explicitly stating racial/ethnic information, the ethnic composition of the sample could not be determined. Reasons for referral to the Child Advocacy Centre included experience(s) with one or more of the following (categories are not mutually exclusive): sexual abuse (n = 77), physical abuse (n = 31), neglect (n = 27), exposure to domestic violence (n = 27), sexualized behavior (n = 18), other (n = 27; i.e., emotional abuse, exposure to drug use, and witnessing the abuse of another child).

Table 1 Descriptive characteristics of the sample (n = 118)

Procedure

Two research assistants, blind to study hypotheses (Vassar & Holzmann, 2013), conducted the data extraction for the current study. Following Gearing, Mian, Barber, and Ickowicz’s (2006) recommended guidelines for retrospective chart reviews, a standardized data extraction protocol was developed and piloted on 10 files, with adjustments made as needed. The research assistants were considered adequately trained once interrater reliability with a senior coder on primary extraction variables was greater than 80%, as recommended by Huffhines et al. (2016), and any areas of disagreement were reviewed together. The research assistants extracted demographic information, as well as information about maltreatment history, presenting clinical symptoms, and protective factors. Data were extracted from any of the following: standard intake record form, clinician reports, case notes, questionnaires completed by children and families, and any medical documents included in the case files. Data extraction was monitored over the course of the study by a registered doctoral-level psychologist. Biweekly supervision was also provided to the research assistants to discuss any concerns they had related to reading the case files as well as any vicarious trauma that may have arisen from reading the case files. Twenty percent of extractions were double coded by an independent second coder for interrater reliability purposes (Hruschka et al., 2004).

Measures

Demographic Information

Demographic information was gathered from an intake form completed by an intake worker at the time of referral, which includes information on child age, child gender, presenting clinical problems, abuse type experienced, and family composition.

Risk Factors

Risk factors examined included adverse childhood experiences and child presenting clinical symptoms at the time of intake.

ACEs

ACEs were measured by the ACEs Questionnaire (Felitti et al., 1998), which retrospectively assesses for current or past exposure to 10 risk factors experienced in childhood: emotional abuse, physical abuse, sexual abuse, emotional neglect, physical neglect, parental separation or divorce, domestic violence, household member substance misuse, household member mental illness or attempted suicide, and incarceration of household member. This questionnaire has demonstrated strong predictive validity in previous child maltreatment literature (Finkelhor, Shattuck, Turner, & Hamby, 2013) and has been previously used in a file review context (Jamora et al., 2009). Using intake information and clinician notes, research assistants coded each ACE as “0” when not present in the child’s history or file and “1” when present. Most of the information regarding ACEs was present in the intake form, which asked referral sources to state the child’s maltreatment history; however, occasionally, clinician notes indicated that the child disclosed an ACE that was not mentioned at intake and this disclosure was also extracted. ACEs were summed and interrater reliability for total ACE scores was excellent (ICC = .94). All discrepancies were resolved via consensus. As detailed in Table 2, the mean ACE score was 4.36 (SD = 2.45).

Table 2 ACEs, presenting symptoms, and resiliency descriptive statistics

Presenting Clinical Concerns

Child presenting clinical symptoms were coded from the intake form, which measured a number of presenting clinical concerns often associated with child maltreatment (Wherry & Dunlop, 2018) and reflect many symptoms that are associated with a diagnosis of post-traumatic stress disorder (American Psychiatric Association, 2013). These presenting symptoms include: physical aggression, oppositional behavior; sexualized acting out; anxiety or fearfulness; nightmares or sleep disturbances; changes in weight, eating, or appetite; preoccupation with traumatic event or inability to stop thinking about the abuse; feelings of guilt or shame about the abuse; persistent sadness or withdrawal; self-harm or thoughts of suicide; strained relationships with caregivers; and substance misuse. The total possible cumulative number of presenting clinical symptoms was 12 and symptoms were coded as 0 = “symptom not present” and 1 = “symptom present.” Interrater agreement for the number of presenting clinical symptoms was good (ICC = .90), and any discrepancies were resolved via consensus. On average, the mean total presenting clinical concerns was 5.36 (SD = 2.32).

Protective Factors

Child protective factors were evaluated using an adaptation of the Child and Youth Resilience Measure (CYRM-28; Ungar & Liebenberg, 2011) for the purposes of the file review methodology. The CYRM identifies eight overall protective factors pertaining to the individual child (i.e., personal skills, peer support, and social skills), caregiver (i.e., physical and psychological caregiving), and context variables (i.e., spiritual, educational, and cultural support). Protective factors were scored by research assistants using information available in files (e.g., intake forms and clinician notes from assessment and treatment sessions). A breakdown of the specific items extracted for the current study can be found in Table 3. Due to a low rate of entry for spiritual and cultural support variables, these items were excluded from our protective factor cumulative score. Scores ranging from 0 to 1 were provided for each of the 6 protective factors where “0” indicates not present and “1” indicates present. A total score ranging from 0 to 6 was obtained (M = 4.91, SD = 1.24). A high degree of interrater agreement was achieved for the total score of protective factors (ICC = .93).

Table 3 CYRM-26 adapted resilience coding

Approximately one-quarter (26%) of children were missing data for 2 or more protective factor items due to inadequate information in case files. To preserve sample size and ensure the sums of protective factors were not biased by missing information, a total protective factor score (ranging from 0 to 6) was used for those with values for at least 5 items.

Treatment Dropout

Child treatment dropout was determined by the clinician and was noted in the closing note of the file as to whether the child had completed the recommended treatment or not. Child treatment dropout was coded as follows: 0 = “completed,” 1 = “dropped out.” As per Gopalan et al. (2010), dropout was determined to occur when families discontinued treatment explicitly or did not attend further appointments despite the clinician’s judgment that the child and family would benefit from services. Of the families who were recommended treatment within the CAS, 38% dropped out. Reasons for dropping out included: scheduling difficulties (n = 2), not being interested in treatment or deeming it unnecessary (n = 12), feeling overwhelmed by treatment (n = 1), financial barriers to attending (n = 1), and parents or caregivers being unable or unwilling to attend regularly or follow the recommendation for treatment (n = 29).

Statistical Analyses

Prior to analyses, t tests comparing children included to those who were not included in the current study were conducted in addition to descriptive statistics and bivariate correlations between variables of interest. To address the study hypotheses, regression analyses were conducted to model the binary variable of treatment dropout (with treatment dropout as the reference group) using child age, ACE score, number of presenting clinical concerns, and number of protective factors as predictors. All analyses and descriptive statistics were performed using SPSS 25.0 and Mplus 8.0 software. A model was run on all participants for whom there was data available regarding treatment completion status (n = 118). The covariances among predictors were included in the model. Within Mplus, the Full Information Maximum Likelihood (FIML) estimator was used to model missing data. Specifically, data was missing for 27% (n = 32) of participants for protective factors. FIML is an effective technique that uses all available data from each individual to estimate their likelihood function and is considered superior to listwise and pairwise deletion as it produces unbiased parameter estimates and their standard errors (Schafer & Graham, 2002).

Results

Group comparisons revealed that the children who were not included in analyses due to lack of treatment completion information (n = 58) did not significantly differ from those who were included (n = 118) in age (t(174) = − 0.20, p = .845), number of presenting clinical symptoms (t(174) = 0.81, p = .417), ACE score (t(174) = − 0.05, p = .960), or number of protective factors (t(174) = − 1.56, p = .121). Bivariate correlational analyses between the potential factors contributing to treatment dropout are presented in Table 4. Child age was positively correlated with the number of presenting clinical symptoms (r = .24, p < .05), ACE score was negatively correlated with the number of protective factors (r = − .46, p < .001) and positively correlated with the number of presenting clinical symptoms (r = .25, p < .001). The number of protective factors was negatively correlated with the number of presenting clinical symptoms (r = − .31, p < .01).

Table 4 Correlations among child age, ACE score, protective factors, and number of presenting symptoms (N = 118)

Risk and Protective Factors for Treatment Dropout

A regression was conducted to model the binary variable of treatment dropout, using treatment dropout as the reference group. Predictor variables included child age, ACE score, number of presenting clinical concerns, and number of protective factors. Results from this analysis indicated that the model accounted for 37% of the total variance in dropout (R2 = .37, p = .001). Table 5 presents the partial regression coefficients and their standard errors, odds ratios and their corresponding confidence intervals, and statistical significance of each predictor. Child age and the number of protective factors were both significant predictors of treatment dropout. For each 1-year increase in child age, children were approximately 16% (OR = 1.16, 95% CI [1.02, 1.32]) more likely to drop out of treatment, adjusting for ACE score, presenting clinical concerns, and protective factors. Additionally, for each one unit increase in number of protective factors present, children were 64% (OR = 0.36, 95% CI [0.21, 0.64]) less likely to drop out of treatment, adjusting for child age, ACE score, and presenting clinical concerns. No other predictors in the model were statistically significant.

Table 5 Results from model predicting treatment dropout (n = 118)

Discussion

Completion of treatment is often an integral component of trauma symptom reduction and recovery in children and youth. Despite this, there is a paucity of empirical research examining risk and protective factors related to treatment dropout in children receiving treatment for maltreatment within child abuse clinics. Therefore, the primary aim of the current retrospective file review study was to identify factors that place children and their families at risk for, or protect them from, treatment dropout.

Consistent with study hypotheses, our findings demonstrate that, above and beyond presenting clinical symptoms, ACEs, and child age, protective factors, which included child coping and sharing skills, peer support, social skills, physical and emotional support from caregiver, and educational involvement, reduced the odds of treatment dropout. This finding suggests that, regardless of their presenting clinical symptoms and the number of adverse experiences they have had, children who have more protective factors in place are better able to engage in and complete treatment. The possibility of perpetuated inequality is often referred to as the Matthew effect (Merton, 1968), which suggests that advantages (i.e., protective factors) may accumulate over time and that cumulative advantage drives inequality (DiPrete & Eirich, 2006). In the context of our study, it is possible that children who come into treatment with the cumulative advantage of protective factors go on to benefit most from treatment, while those with fewer miss out on the benefits of therapy due to dropout or non-attendance, which perpetuates inequality. Our findings emphasize the importance of identifying children with few protective resources at the initiation of treatment, as they may require enhanced treatment efforts to build resilience, which may in turn prevent treatment dropout.

Personal skills such as coping adaptively (i.e., avoiding physical violence or verbal aggression and having skills the child knows they are good at) and openness to sharing feelings and experiences are valuable skills when participating in trauma treatment, which includes components that focus on the development of coping skills and a trauma narrative (Cohen & Mannarino, 2008). Completing these components may be challenging for children who are not open to sharing their feelings or have minimal direct coping skills. Children with coping skill deficits could benefit from a more tailored approach that adjusts treatment materials to focus on bolstering coping skills.

Social support from friends and community members can be particularly important for promoting child resilience; however, children who have experienced maltreatment often have impaired social functioning, which may put them at further risk for psychopathology (Alink, Cicchetti, Kim, & Rogosch, 2012). Therefore, including intervention components for children with poor social skills or social withdrawal may help to alleviate the downstream consequences of child maltreatment on social functioning and provide children with extrafamilial support. School engagement is also a well-established individual protective factor for children who have been maltreated (Domhardt, Münzer, Fegert, & Goldbeck, 2014). Liaising with schools to bolster the supports around a child and promote engagement in both treatment and school is an area worthy of further focus. Previous research has demonstrated that multi-systemic approaches to treatment are effective, particularly with vulnerable children and youth, for boosting school engagement and attendance while also improving family functioning and support (Henggeler et al., 1999).

Children depend on their caregivers to attend and engage in treatment, and caregivers play a key role in children’s resiliency. Physical and emotional caregiving and support are vital in improving outcomes for child maltreatment victims (Cohen & Mannarino, 2000; Saywitz, Mannarino, Berliner, & Cohen, 2000; Zajac, Ralston, & Smith, 2015). Parenting-focused treatments that maximize the support caregivers can provide for their child have a demonstrated impact on child and parent outcomes (Elliott & Carnes, 2001) and may be more effective at increasing engagement and reducing symptoms than individual child treatments alone. Further research is needed to determine whether parenting-focused treatments would be as effective as individual child therapy in terms of treatment engagement and outcomes. Screening caregiver functioning and parenting concerns prior to child treatment may help to identify caregivers who could benefit from targeted parent-focused treatments which would, in turn, provide more support for children and increase the likelihood of completion (Ingoldsby, 2010; Werba, Eyberg, Boggs, & Algina, 2006). Braiding parent-focused and child-focused treatments when there is a need for more direct intervention with parents may be necessary in order for the child’s individual treatment to progress and be completed.

Contrary to expectations, the number of presenting clinical symptoms and the accumulation of multiple ACEs were not associated with treatment dropout, after controlling for child age and protective factors in the current study. Although surprising, this finding can be interpreted as a “good news story”; despite the risk associated with multiple ACEs and presenting clinical symptoms, protective factors may lessen the association between these risk factors and treatment dropout. However, it may be that specific ACEs or presenting clinical symptoms, when examined individually, may matter more than others for treatment outcomes. Future research should examine whether individual ACEs, or subtypes of ACEs, such as exposure to household dysfunction (e.g., family member substance misuse or mental illness) or child maltreatment (physical, sexual, or emotional abuse and neglect), are associated with treatment dropout or lower engagement. For example, previous literature has demonstrated the importance of substance use and parental mental illness for treatment completion within a child maltreatment setting (Damashek, Doughty, Ware, & Silovsky, 2011). Parental substance abuse and mental illness create an overall context of risk that can impair parenting (Belsky, 1984; Eiden, Edwards, & Leonard, 2002), supervision and monitoring (Hadley et al., 2011; Johnson & Leff, 1999), and maintenance of regular routines (Dawe, Harnett, & Frye, 2008). As caregivers are often the gateway through which children access treatment, these deficits could contribute to difficulties attending treatment regularly and may represent barriers to treatment completion. Clinically, it is important to evaluate the family context and the possibility of household dysfunction hindering engagement and retention in the treatment process. Ensuring that parents with mental illness or substance use problems are receiving adequate support to cope sufficiently and continue treatment with their child may hold promise and is an avenue for future maltreatment treatment research.

Finally, child age was found to be a risk factor for treatment dropout. Specifically, we found that older children were more likely to drop out than younger children, which corresponds with previous research on treatment dropout in child maltreatment samples (Celano et al., 2018; Fraynt et al., 2014; Wamser-Nanney & Steinzor, 2016). As discussed by Celano et al. (2018), this finding may be the result of reduced caregiver authority as children age. More simply, younger children often rely on their caregivers to dictate their schedules and older children may be able to make the decision to withdraw from treatment on their own. However, few studies to date discuss possible retention strategies specifically for adolescents in child maltreatment treatment, which highlights an important area for future research.

Previous research on practice elements that enhance engagement in child mental health services has offered a number of potential strategies that align well with the findings from our study. For example, findings from Lindsey et al. (2014) suggest that clinicians should assess the barriers that may prevent youth and their families from participating in treatment (e.g., transportation, stigma), include friends or relatives in treatment planning to strengthen the child’s support network, and use exercises that focus on enhancing caregivers’ coping abilities to directly and indirectly increase family participation in treatment. Staudt (2007) also outlines a number of interventions and strategies that have been found to improve appointment keeping in families with high-risk children seeking treatment.

Study Limitations and Future Directions

The current study outlines important risk factors for treatment dropout for clinicians to be aware of when treating children who have experienced maltreatment; however, a number of limitations should be considered. First and foremost, while our sample size was representative of the annual CAS clinic population, Pedhazur (1997) suggests that logistic regression analyses require a minimum of 30 participants per parameter. Therefore, our sample size may not have had adequate power to detect the effect of ACEs and child presenting clinical symptoms on treatment dropout, given that we needed at least 120 participants. Due to our restricted sample size, we chose to examine the multiplicity of potential risk and protective factors on treatment dropout instead of specific influences on treatment dropout; therefore, we were unable to identify which specific factors account most for dropout such as treatment modality (e.g., whether parenting focused or not); however, this is an important avenue for future research. Furthermore, child maltreatment literature typically examines the impact of the relationship between the child and perpetrator on children’s outcomes (Kiser et al., 2014). We did not examine whether the child’s relationship to the perpetrator was associated with treatment dropout due to our limited sample size and a lack of information about whether or not the perpetrator was engaged in the treatment process with the child. Future studies with more fine-grained analyses on whether specific perpetrator relationships have consequences for treatment dropout rates should be conducted.

Second, the measures we used to quantify risk and protective factors (i.e., ACEs Questionnaire and CYRM-28) were not exhaustive and were limited by the information that was provided in individual case files, such as intake forms and clinician reports, and some ACEs and protective factors may not have been identified. Indeed, the validity of the study relied on clinicians and intake workers gathering the necessary information and entering it into children’s case files as well as accurate reports from the referral source. Furthermore, it could be the case that treatment itself impacted the number of protective factors that clinicians reported in their files; therefore, research that measures protective factors prior to and throughout treatment will be important to parse apart how protective factors influence treatment outcomes. Some risk and protective factors that we did not code for but, based on the broader child treatment literature (de Haan et al., 2013), also merit future investigation include clinician characteristics and child ethnicity status. More research including individual-, caregiver-, contextual-, and treatment-specific factors as predictors of treatment dropout is needed.

Third, in our study, the referral source was usually the one to report on the types of adversity a child had experienced, and they were not administered a formal ACEs questionnaire which could lead to inaccuracies in the reports. However, because the current study was conducted at a Child Advocacy Centre, there is open communication with police and child welfare, and it is more likely that cases would be substantiated. The multidisciplinary nature of the Child Advocacy Centre from which we collected data lends credence to the validity of children’s ACE scores in our study.

Fourth, the reasons families drop out of treatment are variedand thus require further examination. Moreover, in cases where there was no further contact with families, reasons for dropout were not always known. It is possible that families who dropped out of treatment benefited from the sessions they did attend. These families may be qualitatively different from families who attended few sessions and engaged minimally in treatment with no benefit. Since nearly a quarter of families were deemed to not need treatment or were referred elsewhere for treatment and subsequently excluded from further analyses, little is known about whether later treatment was needed or about the treatment outcomes at the referral sites. We were also unable to identify factors specific to the type of treatment families were engaged in. It may be the case that certain modalities and their components, such as creating a trauma narrative in TF-CBT or a specific therapeutic module from COS-P, are particularly prone to attrition within the child maltreatment population. Additional research is needed to understand the more precise mechanisms leading to treatment dropout.

Finally, there are confounding factors related to the specific data obtained for this study, including level of clinician training, services available and accessed, and type of referrals typical of this location (i.e., sexual abuse). Results from this study, therefore, may not apply broadly to child maltreatment settings; however, the nature of the sample and setting accurately reflect clinical settings, which is often more realistic and generalizable to practice than clinical trials.

Conclusions

Presently, there is a dearth of literature examining factors related to treatment engagement in children who have experienced maltreatment. Using a case file review methodology, this study served as an investigation into factors related to treatment dropout among children receiving therapy after experiencing maltreatment. Older children were found to be at an increased risk for treatment dropout, and protective factors mitigated the risk of treatment dropout. Identification and provision of resources specifically targeting individual, caregiver, and contextual deficits may help mitigate the risk of dropout and ensure children get the full benefit of treatment. Despite the adversity faced by children who have been maltreated, protective factors could offset damaging outcomes and enhance treatment success. Addressing specific deficiencies and barriers to treatment engagement and completion should be integrated into services provided to children who have been maltreated and their families in order to foster recovery and enhance support.

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Acknowledgments

We acknowledge the staff at the Child Abuse Service and Alberta Health Services for their collaboration in this project. Research support was provided to Dr. Madigan by the Alberta Children’s Hospital Foundation and the Canada Research Chairs program. Dr. Racine was supported by a Postdoctoral Trainee Award from the Alberta Children’s Hospital Research Institute, the Cumming School of Medicine, and the Social Sciences and Humanities Research Council. Funding sources had no role in publication-related decisions.

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Correspondence to Sheri Madigan.

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Ethics approval for the current study was obtained from the institutional review board and a waiver of consent for retrospective file review was obtained.

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Eirich, R., Racine, N., Garfinkel, D. et al. Risk and Protective Factors for Treatment Dropout in a Child Maltreatment Population. ADV RES SCI 1, 165–177 (2020). https://doi.org/10.1007/s42844-020-00011-9

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Keywords

  • Child maltreatment
  • Resilience
  • Treatment
  • Dropout
  • Risk