Cumulative risk effect of household dysfunction for child maltreatment after intensive intervention of the child protection system in Japan: a longitudinal analysis
Ohashi et al. Environmental Health and Preventive Medicine
Cumulative risk effect of household dysfunction for child maltreatment after intensive intervention of the child protection system in Japan: a longitudinal analysis
Hirotsuna Ohashi 0
Ichiro Wada 1 2
Yui Yamaoka 4
Ryoko Nakajima-Yamaguchi 3
Yasukazu Ogai 3
Nobuaki Morita 3
0 Department of Social Psychiatry and Mental Health, Faculty of Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577 , Japan
1 Aiiku Research Institute, Imperial Gift Foundation Boshi-Aiiku-Kai , 5-6-8 Minami-Azabu, Minato-Ward, Tokyo , Japan
2 Department of Social Welfare, Hanazono University , 8-1 Nishinokyo Tsubonouchi-cho, Nakagyo-ku, Kyoto 604-8456 , Japan
3 Department of Social Psychiatry and Mental Health, Faculty of Medicine, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577 , Japan
4 Department of Health Service Research, Faculty of Medicine, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577 , Japan
Background: Building an effective casework system for child maltreatment is a global issue. We estimated the effect of household dysfunction (i.e., interparental violence, caregiver mental health problems, and caregiver substance abuse) on child maltreatment to understand how to advance the current framework of child welfare. Methods: The sample comprised 759 children (1- to 17-year-old; mean age was 10.6; 404 boys and 355 girls) placed in temporary custody units (one of the strongest intervention of the Japanese child protection system). Caseworkers from 180 units across 43 prefectures completed questionnaires on children and their family and were asked whether a child maltreatment report had been made after cancelation of custody in a 15-month follow-up period. The relations of household dysfunction and maltreatment reports were assessed using the Cox proportional hazard model. Results: About half (48.4%) of the children had been placed in the unit because of maltreatment, and 88.3% had a history of victimization. Seventy-six cases had maltreatment reports after cancelation. We entered household dysfunction variables individually into the model, and each had a significant relationship with maltreatment reports (hazard ratios for interparental violence, caregiver mental health problem, and substance abuse were 1.69, 1.69, and 2.19, respectively) after covariate adjustment. When treating these three variables as cumulative risk score model of household dysfunction, the hazard ratio increased with increasing number of score (1.96 for score two; 2.35 for score three; score 0 as reference). Conclusions: Greater household dysfunction score is a risk of maltreatment after intensive intervention. It is imperative to construct systems facilitating cooperation between child and adult service sectors and to deliver seamless services to children and families. Our findings provide child protect services with risk-stratified interventions for children at victimization risk and promote adult-focused services to be proactive in prevention or intervention for adults with perpetration risk.
Household dysfunction; Temporary custody; Child maltreatment recurrence; Intimate partner violence; Substance abuse; Mental health; Multi-type maltreatment; Adverse childhood experience
The demands placed on the Japanese child protection
system (CPS) have been growing over the last decade. Child
guidance centers (CGCs), which are the primary agencies
for child protection in Japan, received 89,810 reports of
maltreatment in 2014—2.6 times the number 10 years prior
]. It is not uncommon for each social worker to handle
more than 100 cases annually. Such an overload has been
associated with a substantial number of maltreatment
occurrence after CGC involvement, which is an issue of a
great public concern. A more sophisticated assessment
method is required to prevent adverse incidents.
Numerous studies have identified risk factors for cause
of child maltreatment at multiple levels applying
ecological-transactional model [
]. At ontogenic level,
parent factors include mental health [
] and substance abuse
]; at microsystemic level, child factors include younger
3, 6, 7
], disability , and behavior problems [
6, 9, 10
and family factors include being from a single-parent or
step-parent family [
3, 6, 7
], experiencing intimate partner
violence (IPV) and conflict [
5, 8, 11
]; at exosystemic level,
community factors include poverty [
3, 5, 10
] and isolation
]. Additionally, for maltreatment recurrence, the
characteristics of the incidence (e.g., types or number of
previous episodes of maltreatment) [
], the CPS
3, 6, 11
], and post-investigation services [
3, 6, 10,
] also contribute.
These risk factors are shown to be interrelated rather
than occurring independently [
]. When there are
significant interrelations between a group of variables, one
way to avoid confounds in estimating their effects is
treating them as cumulative variables instead of individual
variables. In such strategy, each item is converted into a
dichotomous 0 or 1 score and the summed score is
entered in analyses . Although explanatory power of
each item is lost and equally weighted, we can examine
multiple items simultaneously and avoid distorting view of
any single item as prominent. Begle et al. estimated
parental child maltreatment potential using path analysis based
on Belsky’s developmental-ecological model and
compared with a model using cumulative risk score [
author concluded that cumulative risk score model was
better in fit than path model. In addition, cumulative score
does not capitalize sample dependent variables and have
generality across studies. The other advantage of this
approach is the reduction of the degrees of freedom in
There are extensively used cumulative risk score
approaches. Averse childhood experience (ACE) is a
commonly used measure, which reflects the amount
rather than the severity of exposure [
]. When using
ACEs, researchers obtain data on experiences of
childhood maltreatment (i.e., emotional, physical, and sexual
abuse and physical and emotional neglect) and household
dysfunction (e.g., caregivers’ substance abuse, mental
illness, violent treatment of mother, criminal behavior,
parental separation) [
] and use a cumulative stressor
model examining the effect of the number of ACEs (ACE
score) on outcomes. Studies have indicated that the ACE
score has a long-term impact on health and functional
Number of different types of maltreatment (i.e.,
multitype maltreatment (MTM) [
]), which is contained in
ACEs, is considered a valid measure of the degree of
victimization chronicity and is a better predictor of the
victim’s status when compared to using only a specific
type of maltreatment [
]. It has been demonstrated as
a predictor of mental health [
] and behavior
problems in childhood and adulthood [
For predictor of child maltreatment, there are some
studies using cumulative risk score approach. Wekerle et
al. focused relationship between child maltreatment
substantiation and six caregiver vulnerability items, such as
substance abuse, criminal activities, mental or physical
health issue, and lack of social support [
]. They found
that total number of caregiver vulnerabilities was better
predictor of maltreatment substantiation than any single
item. In aforementioned Begle et al.’s study, the authors
used 20 items in the risk score for maltreatment potential
which included characteristics of parent, child, household,
and neighborhood [
]. In the other studies, case type,
case duration, and closure result [
] or offender’s history
of child maltreatment victimization and the absence of
adult watch over the child in community [
] were used
in the score that related to child maltreatment recurrence.
There are some limitations in these studies for
maltreatment predictors. The items included in cumulative score
system were different in each study, and meanings of
some items are different in culture or social structure.
Thus, it is difficult to treat as generalized measure.
In contrast, adapting a commonly used measure such as
ACEs is an easy way to generalize estimation across
studies. Among ACEs, it is important to focus on household
dysfunction (HD), namely intimate partner violence (IPV),
substance abuse, and mental illness, because caregivers
exhibiting those risks are likely to be involved with
medical and social services but are difficult to treat only
by the child protective system. Although these factors are
important to consider in casework, it can be difficult to
use them as integral and weighting clues for delivering
appropriate services. Nevertheless, there is little literature
focusing on the impact of household dysfunction in child
maltreatment casework [
Our research questions are as follows. First, does household
dysfunction predict future child maltreatment occurrence?
Relatedly, does MTM influence incidence of maltreatment
reports? Although some studies have indicated a
relationship between MTM and maltreatment recurrence [
relationship remains mostly unclear. Next, does household
dysfunction predict future child maltreatment occurrence
after adjustment of MTM? We hypothesized that the effect
of household dysfunction on maltreatment recurrence
would be mediated by current maltreatment status. The
results would indicate that failure of casework does not
only depend on the maltreatment status but also on the
caregiver’s condition. Finally, does the cumulative effect of
MTM and household dysfunction contribute to future
maltreatment occurrence? This would help in identifying
the usefulness of the ACE score in assessing the prognosis
of child maltreatment casework.
The current study utilized a longitudinal, non-experimental
design. This study was conducted as a part of a nationwide
surveillance of temporary custody units in CGCs in 2014,
which was in turn part of a child welfare research project.
Procedure and participants
CGCs are not only specially suited to handling child
maltreatment cases but also dealing with the health and
behavioral problems of children and caregiver’s adversity.
When there is evidence of an urgent need to provide an
alternative environment for a child, CGCs will place the
child in a temporary custody unit and engage in
investigation and treatment of the child and family. After
cancelation of custody, the child either receives in-home services
after sending back to their home or receives continuous
treatment in out-of-home care settings (i.e., institutional or
foster parental care). The subjects of the current study were
children who had had entered temporary custody between
August 1 and 31, 2014. We included only those stayed for
more than 3 days, because important information is likely
to be missed when children released within few days.
Before starting surveillance, all 207 CGCs in Japan,
which spanned 47 prefectures, were contacted to request
their participation. The objectives and procedures of the
study were explained to the facility heads. One hundred
and eighty facilities across 43 prefectures agreed to
participate by returning the reply form (participation rate, 86.
9%). The caseworkers in the participating facilities
completed a questionnaire about the selected children’s
cases on three time points, and then, they sent to
researchers. The questionnaire assessed various aspects of
case records, such as information on the selected child,
their parent(s), family environment, history of CGC
involvement, and the details of the current casework.
Production of questionnaire and data collection were
provided by the Aiiku Research Institute (previously the
Japan Child and Family Research Institute).
The participants were children who had had entered
temporary custody between August 1 and 31, 2014. We
included only those who stayed for more than 3 days,
because essential information is likely to be missed when
children are released within few days. We collected
information at three time points: first, about the day of
the placement; second, about the day of the cancelation
of temporary custody. According to the Japanese Child
Welfare Act, “The period for temporary custody … shall
not exceed 2 months …” [
]; therefore, when the child’s
custody exceeded the 2-month period, we collected data
on the 60th day of their placement. This yielded a total
of 1081 possible cases. For the third point, the
caseworkers completed a follow-up questionnaire on each
index child’s condition in January 2015 (about 15 months
after the child’s placement). As the government
recommends that CGCs should continue providing services for
at least 6 months [
], if the casework was terminated
before January 2015, the follow-up information reflected
their condition at the sixth month after the placement.
The information was given for a total of 759 cases (70.
2% of 1081 cases).
The dependent variable was the existence of
maltreatment report after temporary custody cancelation. This
was collected from CGC administrative records and
coded as present = 1 or not = 0. The date of the report
was also obtained.
Three types of household dysfunction (IPV, caregiver
mental illness, and caregiver substance abuse) and four
types of child maltreatment (physical, emotional, and sexual
abuse and neglect) were included as independent variables.
In Japan, even though children’s exposure to IPV is defined
as emotional maltreatment, numerous cases will be closed
without sufficient investigation as “children’s problems.”
We considered IPV as an aspect of household dysfunction
rather than of child maltreatment. Each variable was coded
dichotomously. The questions about household dysfunction
asked separately for the father and mother were
integrated—if neither caregiver had the problem, the case
was coded as absent = 0, otherwise coded as present = 1.
Japanese national guidelines classify child maltreatment
into four categories: physical abuse, emotional abuse, sexual
abuse, and neglect [
]. We coded child maltreatment
history for each four subtypes dichotomously, present = 1
or absent = 0. Next, we created three cumulative scores: the
number of household dysfunction variables (HD score), the
number of maltreatment types (MTM score), and a sum of
these two cumulative variables.
We selected six covariates from a literature review and the
results of a bivariate analysis: age, sex (reference group was
male), receipt of public assistance (proxy of economic
status), amount of prior CPS involvement, type of
postcancelation treatment (i.e., in-home service or out-of-home
service; the former was the reference), and length of stay in
temporary custody. We believed that the probability of
maltreatment occurrence would be lower if the length of
stay was longer, because the observation period of this
study was short.
All analyses were performed with R (version 3.2.0 [2015–
04–16]; the R Foundation for Statistical Computing). The
Cox proportional hazard model was used to investigate the
relationship between the independent variables and
incidence of maltreatment report after cancelation of
temporary custody while controlling for the covariates. To validate
the selection of covariates, we conducted a series of partial
likelihood ratio and Wald tests according to the purposeful
selection method provided by Hosmer et al. [
proportional hazard assumption was evaluated using
graphical diagnostics. Overall goodness-of-fit of each model was
evaluated by comparing observed and expected numbers of
events calculated from martingale residuals in ten groups
based on risk score.
Most missing data resulted from CGC workers being
unable to obtain sufficient information by the time to
return the questionnaire. One hundred eighteen out of the
759 records (15.5%) were incomplete to some degree. Most
missing data were for economic status of family (n = 37),
followed by caregiver divorce (n = 17), and family structure
(n = 7). To prevent data loss from listwise deletion, we filled
in missing values using the single imputation method
(SIM). To fill in the parent composition item, we coded
missing values as a separate category (“unknown”).
However, because this method might produce biased results, we
employed the multiple imputation (MI) method to further
validate the findings [
]. We performed 20 iterations for
30 multiple imputed datasets each. All MI calculations were
performed in R using the default settings of the mice 2.25
]. Model parameters were estimated with
multivariate Cox regressions applied to each imputed dataset
separately. These repeated estimates and their standard
errors were combined into final estimates using Rubin’s
rule, which ultimately yielded an MI dataset of 759 cases.
Table 1 describes the main characteristics of the sample.
The mean age of the children at the time of placement was
10.6 years. Half of the children were boys, and 7.5% were
non-Japanese. Six out of every ten (58.8%) children were
from single-parent families, while around one fifth (20.2%)
of children lived with both biological parents. One third
(30.8%) of cases were from households receiving public
assistance. Regarding reasons for placement, almost half
(48.4%) had been placed in temporary custody for
protection from maltreatment. The other common reasons were
parenting problems (28.6%) and delinquency (14.6%). In
total, children with history of any maltreatment accounted
for 88.3%; 57.4% of children had a history of physical abuse,
71.3% had emotional abuse, 10.1% had sexual abuse, and
63.2% had neglect. More than one third (37.2%) of children
had three types of maltreatment (MTM), in contrast with
one eighth (12.8%) were 0—MTM. For household
dysfunction, 46.6% of cases had reports of IPV, 43.5% had mental
health problems, and 22.5% had substance abuse. Two
thirds had some household dysfunction. The number of
children with MTM + HD scores 0, 1, 2, 3, 4, 5, and 6 were
49, 79, 134, 197, 151, 116, and 33, respectively.
Cox proportional hazard model
Overall, 76 of the 759 cases had reports of maltreatment
within 15-month follow-up period. Bivariate Cox
regression models with 30 multiple imputed datasets (Table 2)
revealed that the following variables had significant
relationships with this outcome: age (pooled hazard ratio
[HR], 0.90, 95% confidence interval [CI] [0.85, 0.95]);
interparental violence, caregiver mental health problem,
and caregiver substance abuse (pooled HR, 1.74, 95% CI
[1.10, 2.74]; 1.67, 95% CI [1.06, 2.63]; and 2.13, 95% CI
[1.34, 3.40], respectively); physical abuse, emotional
abuse, and neglect (pooled HR, 2.71, 95% CI [1.58, 4.65];
3.08, 95% CI [1.54, 6.17]; and 2.92, 95% CI [1.61, 5.31],
respectively); and use of the out-of-home
posttemporary custody service (pooled HR, 0.21, 95% CI
[0.11, 0.40]). History of sexual abuse and the amount
of prior CPS involvement was marginally significantly
associated with the outcome (p < .25).
Next, we constructed seven Cox regression models, each
with one household dysfunction or child maltreatment
variable as the independent variable and age, amount of
prior CPS involvement before custody, duration of stay in
custody, and post-temporary custody service as covariates.
Table 3 shows the associations of each independent variable
with the outcome, after adjusting for these covariates.
Sexual abuse was the only variable without significant
relationship with the outcome.
Then, we entered the HD and MTM scores (except for
sexual abuse, given that no relationship with the outcome;
Table 4). The HD score was entered as a four-level (0, 1, 2,
and 3) categorical variable with 0 as the reference. For the
MTM score, we combined levels 0 and 1 because of the
small size; thus, it comprised three levels of 0 to 1, 2, and
CGC child guidance center (out-of-home, therapeutic institutions, or foster
parents), HD household dysfunction (sum of each of the three individual
categories of interparental violence, parental substance abuse, and mental
health problem), MTM multi-type maltreatment (number of types of maltreatment,
i.e., physical abuse, emotional abuse, and neglect)
3, with 0 to 1 as the reference. For the HD score, the
pooled HR had a graded tendency with increasing level
(HR was 2.39, 95% CI [1.26, 4.54] for score 2 and 3.17,
95% CI [1.45, 6.92] for score 3). Regarding the MTM
score, the HRs for scores 2 and 3 were 2.41, 95% CI [1.09,
5.30] and 6.01, 95% CI [2.91, 12.41], respectively.
Finally, we entered the HD and MTM scores
simultaneously (Table 5). When we adjusted for MTM in this
model, HD score still significantly predicted the
outcome, with the pooled HRs showing a graded tendency
(HR for score 2 was 1.96, 95% CI [1.03, 3.73]; HR for
score 3 was 2.35, 95% CI [1.07, 5.16]). Then, we added
Note: All analyses were performed with missing values imputed by multiple imputation method
CGC child guidance center (out-of-home, therapeutic institutions, or foster parents), HR hazard ratio, CI confidence interval
the two scores and entered them as a categorical
variable, which was grouped into four levels according to
sample size (0 to 1, 2, 3 to 4, and 5 to 6; the reference
was 0 to 1). The summed HD score and MTM scores
had also a significant relationship with outcome, and its
pooled HRs showed a graded tendency with increasing
level (HRs for scores of 3 to 4 and 5 to 6 were 5.00, 95%
CI [1.53, 16.37] and 11.41, 95% CI [3.47, 37.52],
respectively). Among the covariates, age (HR, 0.93, 95% CI
[0.88, 0.99]) and a post-temporary custody service of
out-of-home service (HR, 0.24, 95% CI [0.13, 0.47])
had significant relationships with the outcome.
Validation with single imputation method dataset
We then conducted the above analysis using the single
imputation method dataset that was coded missing values
as a separate category, “unknown”. The HRs of the different
levels of the variables exhibited a graded tendency and were
larger than the HRs calculated using the SIM. For example,
in the household dysfunction model (Additional file 1:
Table S1), the HRs for scores of 2 and 3 were 2.31, 95% CI
[1.21, 4.40] and 3.25, 95% CI [1.48, 7.12], respectively (in
contrast, the HRs in the MI dataset were 2.39 and 3.17; see
Table 4). Similarly, for the composite model (sum of the
HD score and MTM scores, Additional file 1: Table S2), the
HRs for scores 3 to 4 and 5 to 6 were 3.80, 95% CI [1.35,
10.74] and 8.40, 95% CI [2.94, 24.00], respectively (in
contrast, the HRs in the MI dataset were 5.00 and 11.41;
see Table 5). The above findings indicated that while all of
the directions of the coefficients were the same, the size of
the effects were larger in the composite model with the MI
This is the first study to examine maltreatment
occurrence of children placed in temporary custody throughout
Japan. Based on the description of the sample, children
placed in the temporary custody were unique population
as they live in adverse condition. Table 1 shows that more
than half children were from single-parent families and
one third were receiving public assistance. Bivariate model
Note: All models were adjusted for age, amount of prior CPS involvement,
duration of temporary custody, and post-temporary custody service with
missing values imputed by multiple imputation method
HR hazard ratio, CI confidence interval, HD household dysfunction (sum of
each of the three individual categories of interparental violence, parental
substance abuse, and mental health problem), MTM multi-type maltreatment
(number of types of maltreatment, i.e., physical abuse, emotional abuse,
showed (Table 2) that family characteristics such as family
structure and economic status were not associated with
outcome, i.e., maltreatment report within about 1 year
after intensive intervention of temporary custody.
Although those family characteristics have been
considered as presumable risk factor for child maltreatment in
series of precede studies [
3, 5–7, 10
], the sample bias
might make these factors negligible in our analyses. About
90% of children in our study had a history of
maltreatment, regardless of their current reason for placement. In
addition, most of children whose reason for placement
was other than maltreatment had history of child
maltreatment (77.5%). The larger the MTM score, the larger
the number of samples. These results indicate that chronic
] pervaded among placed children.
Conversely, that may indicate that more victimized
children tend to be protected. To substitute MTM + HD
score for ACE, the median of number of the adverse
experience was three, which is larger than general
population. Preceding national survey in other country showed
that half of the respondents had no ACEs and those
reported four or more ACE were 6.2–8.3% [
Summarizing the above, children needed temporary custody is
unique population given exposed to multiple adversity.
Regarding seven regression models for each HDs or
maltreatment variables (Table 3), adjusted HRs were
higher than 1 except for sexual abuse. Some research
has shown that sexual abuse was least likely to be
rereported to CPS agencies when compared to physical
abuse or neglect [
]. In Japan, sexual abuse is
classified as a severe form of maltreatment that requires
strong intervention which might make a lower risk of
future child maltreatment.
Estimating cumulative effect of adversity (Table 4), both
household dysfunction score and MTM score had
significant and dose-response relationship with risk of
maltreatment report, and the effect of household dysfunction was
significant even after adjustment for MTM (Table 5);
children with two HDs and three HDs had twofold
and 2.5-fold higher risk for maltreatment report after
intervention compared to those with no household
dysfunction. This finding is comparable to Wekerle et al.’s
], where the authors showed relationship
between substantiation of maltreatment and number of
household dysfunction in cross-sectional analyses. Our
study is different in that we conducted longitudinal
analyses on children after CPS intervention and estimated the
impact of HDs for CPS re-entry for maltreatment after
adjustment of the handling difficulty of MTM.
When combining these MTM and HD scores (Table 5),
the presence of three types of household dysfunction or
maltreatment (out of all six) led to a fourfold higher risk
when compared with only one item. One study conducted
with young children demonstrated that when a child had
more than four ACEs, their mother was more likely to
exhibit abusive or neglectful parenting behavior [
finding partially coincides with this observation. However,
we cannot confirm whether sexual abuse has the same
relationship, as it was not associated with future
maltreatment reports and thus we did not enter it into the
cumulative variable analysis.
Among the covariates, younger age was related to a
higher risk of a maltreatment report that is compatible
with other studies [
6, 9, 15, 41
]. The other variables, such
as economic status, complicated family structure, or
family size, are not associated with outcome significantly
in bivariate analyses. Although these are indicated as risk
factor of child maltreatment occurrence and chronicity in
general population, it might be not in the case of children
needed advance intervention. Regarding treatment after
cancelation of temporary custody, we found that in-home
services were associated with a higher risk of a
maltreatment report than institutional or foster-parent care. Many
studies have identified several important risk factors such
as intensity of CPS investigation level, service type, and
result of intervention [
10, 49, 51
]. In Japan, children
placed in institutional care are prone to receiving
continuous social protection, and thus, they are not likely to be
exposed to maltreatment again.
Our findings have some implications. First, social workers
might use them to provide risk-stratified interventions for
maltreatment occurrence or recurrence according to the
number of household dysfunction in each case. Moreover,
the sum of the number of household dysfunction and
maltreatment type and the analogue of ACE may be useful
in risk stratification. Next, the child-welfare agency might
be more confident in requesting coordination with
agencies that provide services for adults. Furthermore,
adultfocused services might be more proactive in promoting
interventions for adults who exhibit risks of child
maltreatment, even if the service is never involved with the
index child directly. Because the Japanese CPS is highly
burdened already, collaboration with agencies outside this
system will be helpful. Focusing on caregiver problems
would enable to use resources beyond the framework of
the child welfare system. For example, the agencies
dealing with mental health problems or substance abuse
normally have regular contact with clients and thus can
act as gatekeepers for child maltreatment. A Japanese
study of 1492 patients with mental health problems
including substance abuse found that 9% of patients were
living with their children and 38% of them were rearing
the child(ren) on their own [
]. For such patients,
regardless of the possibility of maltreatment, proactive measures
that help them engage in effective parenting and deliver
ample social resources are needed. Researches have
demonstrated the effectiveness of risk-focused parenting
programs, and that parenting characteristics reduce the
detrimental effects on children’s mental or behavior
]. For IPV exposure, past research showed that
resolution of IPV after CPS involvement was significantly
associated with the child’s mental and behavior outcomes
]. Despite that, a lack of coordination between CPS and
IPV response agencies is not uncommon [
]. In Japan,
because treatment of IPV is beyond the competence of
CGC, and workers tend to consider cases of witness IPV as
“low risk” or safer than other life-threatening maltreatment
incidents, their cases will be closed even without providing
sufficient help to children or families.
Additionally, caregivers experiencing such adversity
might have other vulnerabilities. Mothers engaging in
substance abuse showed that CPS-involved mothers are
likely to be younger, have a lower socioeconomic status,
and have fewer interpersonal resources compared to
those not involved in CPS [
]. Helping IPV victims
requires structural interventions, including the contribution
of economic, politico-legal, and social environmental
factors, and a lack of social support was found to be
associated with mental health and parenting functioning [
When we focus on these HDs, we should expand the links
with other organizations that engage in distinct types of
specialist area beyond child-welfare systems and construct
multidisciplinary measures aimed at uninterrupted
prevention and intervention of child maltreatment in
providing effective casework.
A main limitation was the substantial reduction in sample
size—namely, around 30% of the original sample was
excluded after merging data from the entry and follow-up
period. In this study, the information was obtained from
separately conducted questionnaire survey in three time
points and integrated into longitudinal dataset. Some
CGC disagreed to participate at the third time point and
that made reduce the sample size. Furthermore, some data
had missing values. The small sample size and short
observation period allow for limited conclusions.
Constructing a comprehensive database for CGC-involved
children and their families would allow for more precise
analyses in this field. Additionally, because respondents
were not actually the index child or family, the variables
concerning their experience are likely to be inaccurate,
and the severity of victimization was unknown. By
obtaining this information in future research, we could provide a
more precise guide in constructing effective practice to
reduce the severity and chronicity of child maltreatment.
In order to implement such research, we should construct
self-report system targeted at victimized children and/or
their family member other than perpetrators that might
be feasible when we use computer-assisted interview that
ensure the privacy of participants [
]. Finally, because the
study sample was among the most vulnerable population
in Japan, one must be cautious in generalizing the
findings. Many children in this study were from adverse
environment; one third received public assistance and more
than half were from single-parent family and suffered
from multiple adverse experiences. If we conducted
investigation in children without temporary custody placement,
the items related to family condition might have strong
relationship to outcome, and the group of predictors would
be different from this analyses. Despite these limitations,
this study is valuable in its demonstration of the
importance of number of household dysfunction in predicting
the risk of child maltreatment after intensive intervention.
Our findings suggest that the number of household
dysfunctions is a significant predictor of subsequent
maltreatment report after intensive CPS intervention. This is true
even after adjustment for child maltreatment status and
child, family, and service factors. Given the constellation
of risks, multidisciplinary system expanded beyond the
child welfare system is desired in child maltreatment
Additional file 1: Table S1. Result of analyses using SIM dataset.
Multivariate Cox regression for maltreatment reports after temporary
custody cancelation. Table S2. Result of analyses using SIM dataset.
Multivariate Cox regression for maltreatment report after temporary
custody cancelation. (DOCX 32 kb)
ACE: Adverse childhood experience; CGC: Child guidance center; CPS: Child
protection system; HD: Household dysfunction; IPV: Intimate partner violence;
MI: Multiple imputation; MTM: Multi-type maltreatment; SIM: Single
The authors acknowledge and thank all service providers at the temporary
custody units of the Child Guidance Centers for taking time from their busy
schedule to reply to our questionnaire, as well as the officials of their
facilities who agreed to participate. Support for this work in the collection of
data was provided by the Ministry of Health, Labour and Welfare (Issue of
2014 Child Welfare Research Project, No. 2). We would like to thank Editage
(www.editage.jp) for the English language editing.
This work was supported by Japan Science and Technology Agency.
Availability of data and materials
The data that support the findings of this study are available from Aiiku
Research Institute; however, restrictions apply to the availability of these
data, which were used under license for the current study, and are thus
not publicly available. Data are, however, available from the authors upon
a reasonable request and with permission from the Aiiku Research Institute.
HO analyzed and interpreted the data and was a major contributor in writing the
manuscript. IW designed the study, contributed to the collection and analysis of
data, and assisted in the preparation of the manuscript. NM and YO contributed
to the interpretation of data and assisted in the preparation of the manuscript.
All other authors contributed to the data interpretation and critically reviewed
the manuscript. All authors approved the final version of the manuscript and
agree to be accountable for all aspects of the work in ensuring that questions
related to the accuracy or integrity of any part of the work are appropriately
investigated and resolved.
Ethics approval and consent to participate
The data collection was provided by the Aiiku Research Institute (previously
the Japan Child and Family Research Institute) in the 2013 fiscal year, and
this project was part of the Project, “Overview of Temporary Custody and
Descriptive Investigation for Entered Children.” The Research Ethics
Committee of the Aiiku Research Institute (no. 60) and The Committee of
Medical Ethics, Graduate School of Human-Care Science, Tsukuba University
(no. 898), approved the study protocol. Informed consent was obtained from
all individual participants included in the study.
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
1. Ministry of Health, Labour and Welfare. Handbook of health and welfare statistics . http://www.mhlw.go.jp/english/database/db-hh/3- 2 .html. Accessed 18 Dec 2017 .
2. Belsky J . Child maltreatment: an ecological integration . Am Psychol . 1980 ; 35 : 320 - 35 .
3. Fuller TL . Child safety at reunification: a case-control study of maltreatment recurrence following return home from substitute care . Child Youth Serv Rev . 2005 ; 27 : 1293 - 306 .
4. Wolock I , Magura S. Parental substance abuse as a predictor of child maltreatment re-reports . Child Abuse Negl . 1996 ; 20 : 1183 - 93 .
5. Palusci VJ , Ondersma SJ . Services and recurrence after psychological maltreatment confirmed by child protective services . Child Maltreat . 2012 ; 17 : 153 - 63 .
6. Bae H-O , Solomon PL , Gelles RJ . Multiple child maltreatment recurrence relative to single recurrence and no recurrence . Child Youth Serv Rev . 2009 ; 31 : 617 - 24 .
7. Fuller T , Nieto M. Child welfare services and risk of child maltreatment rereports: do services ameliorate initial risk? Child Youth Serv Rev . 2014 ; 47 : 46 - 54 .
8. DePanfilis D , Zuravin SJ . The effect of services on the recurrence of child maltreatment . Child Abuse Negl . 2002 ; 26 : 187 - 205 .
9. Hélie S , Laurier C , Pineau-Villeneuve C , Royer M-N . A developmental approach to the risk of a first recurrence in child protective services . Child Abuse Negl . 2013 ; 37 : 1132 - 41 .
10. Li D , Chu CM , Ng WC , Leong W. Predictors of re-entry into the child protection system in Singapore: a cumulative ecological-transactional risk model . Child Abuse Negl . 2014 ; 38 : 1801 - 12 .
11. Hindley N. Risk factors for recurrence of maltreatment: a systematic review . Arch Dis Child . 2006 ; 91 : 744 - 52 .
12. Wu SS , Ma C-X , Carter RL , Ariet M , Feaver EA , Resnick MB , et al. Risk factors for infant maltreatment: a population-based study . Child Abuse Negl . 2004 ; 28 : 1253 - 64 .
13. Sidebotham P , Heron J , Team AS . Child maltreatment in the children of the nineties: a cohort study of risk factors . Child Abuse Negl . 2006 ; 30 : 497 - 522 .
14. Putnam-Hornstein E , Needell B . Predictors of child protective service contact between birth and age five: an examination of California's 2002 birth cohort . Child Youth Serv Rev . 2011 ; 33 : 1337 - 44 .
15. Fluke JD , Yuan Y-YT , Edwards M. Recurrence of maltreatment: an application of the National Child Abuse and Neglect Data System (NCANDS) . Child Abuse Negl . 1999 ; 23 : 633 - 50 .
16. Dorsey S , Mustillo SA , Farmer EMZ , Elbogen E. Caseworker assessments of risk for recurrent maltreatment: association with case-specific risk factors and re-reports . Child Abuse Negl . 2008 ; 32 : 377 - 91 .
17. Bae H-O , Solomon PL , Gelles RJ , White T . Effect of child protective services system factors on child maltreatment rereporting . Child Welfare . 2010 ; 89 : 33 - 55 .
18. Spaccarelli S , Sandler IN , Roosa M. History of spouse violence against mother: correlated risks and unique effects in child mental health . J Fam Viol . 1994 ; 9 : 79 - 98 .
19. Lamers-Winkelman F , Willemen AM , Visser M. Adverse childhood experiences of referred children exposed to intimate partner violence: consequences for their wellbeing . Child Abuse Negl . 2012 ; 36 : 166 - 79 .
20. Sameroff AJ , Seifer R , McDonough SC . Contextual contributors to the assessment of infant mental health . In: DelCarmen-Wiggins R , Carter AS , editors. Handbook of infant, toddler, and preschool mental health assessment . New York: Oxford University Press; 2004 . p. 61 - 76 .
21. Begle AM , Dumas JE , Hanson RF . Predicting child abuse potential: an empirical investigation of two theoretical frameworks . J Clin Child Adolesc Psychol . 2010 ; 39 : 208 - 19 .
22. Felitti VJ , Anda RF , Nordenberg D , Williamson DF , Spitz AM , Edwards V , et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults . Am J Prev Med . 1998 ; 14 : 245 - 58 .
23. Dube SR , Felitti VJ , Dong M , Chapman DP , Giles WH , Anda RF . Childhood abuse, neglect, and household dysfunction and the risk of illicit drug use: the adverse childhood experiences study . Pediatrics . 2003 ; 111 : 564 - 72 .
24. Anda RF , Croft JB , Felitti VJ , Nordenberg D. Adverse childhood experiences and smoking during adolescence and adulthood . JAMA . 1999 ; 282 : 1652 - 8 .
25. Hillis SD , Anda RF , Felitti VJ , Nordenberg D , Marchbanks PA . Adverse childhood experiences and sexually transmitted diseases in men and women: a retrospective study . Pediatrics . 2000 ; 106 : e11 .
26. Hillis SD , Anda RF , Felitti VJ , Marchbanks PA . Adverse childhood experiences and sexual risk behaviors in women: a retrospective cohort study . Fam Plan Perspect . 2001 ; 33 : 206 .
27. Dube SR , Anda RF , Felitti VJ , Chapman DP , Williamson DF , Giles WH . Childhood abuse, household dysfunction, and the risk of attempted suicide throughout the life span: findings from the adverse childhood experiences study . JAMA . 2001 ; 286 : 3089 - 96 .
28. Hillis SD , Anda RF , Dube SR , Felitti VJ , Marchbanks PA , Marks JS . The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death . Pediatrics . 2004 ; 113 : 320 - 7 .
29. Kelly-Irving M , Lepage B , Dedieu D , Bartley M , Blane D , Grosclaude P , et al. Adverse childhood experiences and premature all-cause mortality . Eur J Epidemiol . 2013 ; 28 : 721 - 34 .
30. Bellis MA , Hughes K , Leckenby N , Jones L , Baban A , Kachaeva M , et al. Adverse childhood experiences and associations with health-harming behaviours in young adults: surveys in eight eastern European countries . Bull World Health Organ . 2014 ; 92 : 641 - 55 .
31. Higgins DJ , McCabe MP . Relationships between different types of maltreatment during childhood and adjustment in adulthood . Child Maltreat . 2000 ; 5 : 261 - 72 .
32. Herrenkohl TI , Herrenkohl RC . Examining the overlap and prediction of multiple forms of child maltreatment, stressors, and socioeconomic status: a longitudinal analysis of youth outcomes . J Fam Viol . 2007 ; 22 : 553 - 62 .
33. Vranceanu A-M , Hobfoll SE , Johnson RJ . Child multi-type maltreatment and associated depression and PTSD symptoms: the role of social support and stress . Child Abuse Negl . 2007 ; 31 : 71 - 84 .
34. Mangion M , Buttigieg SC. Multi-type childhood maltreatment: associations with health risk behaviours and mental health problems in adolescence . J Child Serv . 2014 ; 9 : 191 - 206 .
35. Sesar K , Šimić N , Barišić M. Multi-type childhood abuse, strategies of coping, and psychological adaptations in young adults . Croat Med J. 2010 ; 51 : 406 - 16 .
36. Arata CM , Langhinrichsen-Rohling J , Bowers D , O'Brien N. Differential correlates of multi-type maltreatment among urban youth . Child Abuse Negl . 2007 ; 31 : 393 - 415 .
37. Wanklyn SG , Day DM , Hart TA , Girard TA . Cumulative childhood maltreatment and depression among incarcerated youth: impulsivity and hopelessness as potential intervening variables . Child Maltreat . 2012 ; 17 : 306 - 17 .
38. Witt A , Münzer A , Ganser HG , Fegert JM , Goldbeck L , Plener PL . Experience by children and adolescents of more than one type of maltreatment: association of different classes of maltreatment profiles with clinical outcome variables . Child Abuse Negl . 2016 ; 57 : 1 - 11 .
39. Wekerle C , Wall A-M , Leung E , Trocmé N. Cumulative stress and substantiated maltreatment: the importance of caregiver vulnerability and adult partner violence . Child Abuse Negl . 2007 ; 31 : 427 - 43 .
40. Horikawa H , Suguimoto SP , Musumari PM , Techasrivichien T , Ono-Kihara M , Kihara M. Development of a prediction model for child maltreatment recurrence in Japan: a historical cohort study using data from a child guidance center . Child Abuse Negl . 2016 ; 59 : 55 - 65 .
41. Palusci VJ . Risk factors and services for child maltreatment among infants and young children . Child Youth Serv Rev . 2011 ; 33 : 1374 - 82 .
42. Ministry of Health, Labour and Welfare. Child guidance center administration guidance . 1990 . http://www.mhlw.go.jp/bunya/kodomo/pdf/ dv120321- 02 .pdf. Accessed 19 Dec 2017 .
43. Ministry of Health, Labour and Welfare. Help guidelines for the guardian who performed child abuse . 2008 . http://www.mhlw.go.jp/bunya/kodomo/ dv21/01.html. Accessed 19 Dec 2017 .
44. Ministry of Justice. Act on the prevention, etc . of child abuse. 2000 . http:// www.japaneselawtranslation.go.jp/law/detail/?printID=& id=2221&re= 02&vm=02. Accessed 19 Dec 2017 .
45. Hosmer DW , Lemeshow S , May S. Applied survival analysis . New Jersey: Wiley; 2011 .
46. Little RJA , Rubin DB . Statistical analysis with missing data . 2nd ed. New Jersey: Wiley; 2002 .
47. van Buuren S. Flexible imputation of missing data . Boca Raton: CRC Press; 2012 .
48. Bellis MA , Hughes K , Leckenby N , Hardcastle KA , Perkins C , Lowey H . Measuring mortality and the burden of adult disease associated with adverse childhood experiences in England: a national survey . J Public Health (Oxf) . 2015 ; 37 : 445 - 54 .
49. Bae H-O , Solomon PL , Gelles RJ . Abuse type and substantiation status varying by recurrence . Child Youth Serv Rev . 2007 ; 29 : 856 - 69 .
50. McKelvey LM , Whiteside-Mansell L , Conners-Burrow NA , Swindle T , Fitzgerald S . Assessing adverse experiences from infancy through early childhood in home visiting programs . Child Abuse Negl . 2015 ; 51 : 295 - 302 .
51. Hélie S , Poirier M-A , Turcotte D . Risk of maltreatment recurrence after exiting substitute care: impact of placement characteristics . Child Youth Serv Rev . 2014 ; 46 : 257 - 64 .
52. The National Federation of Mental Health and Welfare Party in Japan. Questionnaire on life and treatment of people with mental disorders. (Seishin shōgai ga aru hito no seikatsu to chiryō ni kansuru ankēto) 2011 . https:// seishinhoken.jp/files/view/articles_files/src/4.pdf. Accessed 19 Dec 2017 .
53. Casillas KL , Fauchier A , Derkash BT , Garrido EF . Implementation of evidencebased home visiting programs aimed at reducing child maltreatment: a meta-analytic review . Child Abuse Negl . 2016 ; 53 : 64 - 80 .
54. Campbell KA , Thomas AM , Cook LJ , Keenan HT . Resolution of intimate partner violence and child behavior problems after investigation for suspected child maltreatment . JAMA Pediatr . 2013 ; 167 : 236 - 42 .
55. Jenney A , Mishna F , Alaggia R , Scott K. Doing the right thing? (Re) considering risk assessment and safety planning in child protection work with domestic violence cases . Child Youth Serv Rev . 2014 ; 47 : 92 - 101 .
56. Zannettino L , McLaren H . Domestic violence and child protection: towards a collaborative approach across the two service sectors . Child Fam Soc Work . 2014 ; 19 : 421 - 31 .
57. Lussier K , Laventure M , Bertrand K. Parenting and maternal substance addiction: factors affecting utilization of child protective services . Subst Use Misuse . 2010 ; 45 : 1572 - 88 .
58. Levendosky AA , Graham-Bermann SA . Parenting in battered women: the effects of domestic violence on women and their children . J Fam Viol . 2001 ; 16 : 171 - 92 .
59. Hussain N , Sprague S , Madden K , et al. A comparison of the types of screening tool administration methods used for the detection of intimate partner violence: a systematic review and meta-analysis . Trauma Violence Abuse . 2015 ; 16 : 60 - 9 .