Administrative data linkage as a tool for child maltreatment research

Using data linkage for mental health research in Australia

Data linkage is a powerful tool for understanding the multifaceted needs and priorities of mental health care from the perspective of users and providers. Its potential remains underutilised in Australian settings - the Productivity Commission Inquiry into Mental Health in 2020 highlighted a significant gap: routinely collected administrative data are seldom leveraged in mental health research and service evaluation. In this manuscript, we provide insights into how data linkage has been used in mental health research, the type of questions that can be addressed, the steps involved in conducting data linkage research and the benefits and limitations of the use of this methodology. We propose crucial recommendations for advancing this field including: enhancing education for stakeholders (including the public, data custodians, ethics committees and policy makers); fostering stronger collaborative relationships with individuals with lived experiences throughout the research journey; improving infrastructure and resources for data linkage activities and linking data across sectors to address complex meaningful research questions. Data linkage is not just a method but a critical strategy to transform mental health research and service evaluation, ensuring more informed, effective and holistic mental health care.

Pediatric Self-Harm Injuries and Child Protection Histories

We assessed the child protective services (CPS) histories of children with medical encounters for self-harm (SH) using linked medical and CPS data. Most children with SH had prior CPS reports (61.0%), but few had foster care placements (5.9%). CPS histories may be important to understand, treat, and prevent pediatric SH.

Receipt of parenting, disability, unemployment, and other income support payments in persons aged 16 to 33 years - the associations with child maltreatment

BACKGROUND

Child maltreatment (CM) is a major public health concern with life-long effects. Its impact on income support has rarely been studied.

OBJECTIVE

To examine the association between CM and receipt of income support payments and the budgetary impact for persons 16 to 33 years.

PARTICIPANTS AND SETTING

A South Australian birth cohort, born 1986 to 2004 (n = 339,411).

METHODS

We linked child protection (CP) administrative records with national welfare payment records, ending March 2020. Receipt of income support payments and mean payment amounts were described by CP contact (adjusted for child and family attributes). Budget impact was modelled at the national level.

RESULTS

Adjusted odds ratio (AOR) for receipt of any income support payment was 3.01 (2.95-3.07) for individuals with any CP contact versus no CP contact. Among those receiving any payment, adjusted annualised mean benefit payment was $3754 (US$1446) among individuals with no CP contact, $6262 (US$4,307) in persons with any CP contact, and $9,747 in persons who'd been in OOHC. Cumulative payments modelled from age 16 to 33 years totalled $38,570 (US$26,652) for individuals with no CP contact, and $181,743 (US$125,003) for individuals who'd been in OOHC. Modelled for the Australian population to age 33, the extra cost associated with CP contact added 39 % to the government income support budget.

CONCLUSION

CM is strongly associated with receipt of income support payments. Investment in effective preventive and protective strategies for CP involved children could address this core social determinant of health, while providing budget savings.

From Scientific Research to Practical Implementations: Applications to Improve Data Quality in Child Welfare

Child welfare decisions have life-impacting consequences which, often times, are underpinned by limited or inadequate data and poor quality. Though research of data quality has gained popularity and made advancements in various practical areas, it has not made significant inroads for child welfare fields or data systems. Poor data quality can hinder service decision-making, impacting child behavioral health and well-being as well as increasing unnecessary expenditure of time and resources. Poor data quality can also undermine the validity of research and slow policymaking processes. The purpose of this commentary is to summarize the data quality research base in other fields, describe obstacles and uniqueness to improve data quality in child welfare, and propose necessary steps to scientific research and practical implementation that enables researchers and practitioners to improve the quality of child welfare services based on the enhanced quality of data.

An open-source probabilistic record linkage process for records with family-level information: Simulation study and applied analysis

Research with administrative records involves the challenge of limited information in any single data source to answer policy-related questions. Record linkage provides researchers with a tool to supplement administrative datasets with other information about the same people when identified in separate sources as matched pairs. Several solutions are available for undertaking record linkage, producing linkage keys for merging data sources for positively matched pairs of records. In the current manuscript, we demonstrate a new application of the Python RecordLinkage package to family-based record linkages with machine learning algorithms for probability scoring, which we call probabilistic record linkage for families (PRLF). First, a simulation of administrative records identifies PRLF accuracy with variations in match and data degradation percentages. Accuracy is largely influenced by degradation (e.g., missing data fields, mismatched values) compared to the percentage of simulated matches. Second, an application of data linkage is presented to compare regression model estimate performance across three record linkage solutions (PRLF, ChoiceMaker, and Link Plus). Our findings indicate that all three solutions, when optimized, provide similar results for researchers. Strengths of our process, such as the use of ensemble methods, to improve match accuracy are discussed. We then identify caveats of record linkage in the context of administrative data.

Leveraging Administrative Data to Better Understand and Address Child Maltreatment: A Scoping Review of Data Linkage Studies

BACKGROUND

This scoping review aimed to overview studies that used administrative data linkage in the context of child maltreatment to improve our understanding of the value that data linkage may confer for policy, practice, and research.

METHODS

We searched MEDLINE, Embase, PsycINFO, CINAHL, and ERIC electronic databases in June 2019 and May 2020 for studies that linked two or more datasets (at least one of which was administrative in nature) to study child maltreatment. We report findings with numerical and narrative summary.

RESULTS

We included 121 studies, mainly from the United States or Australia and published in the past decade. Data came primarily from social services and health sectors, and linkage processes and data quality were often not described in sufficient detail to align with current reporting guidelines. Most studies were descriptive in nature and research questions addressed fell under eight themes: descriptive epidemiology, risk factors, outcomes, intergenerational transmission, predictive modelling, intervention/service evaluation, multi-sector involvement, and methodological considerations/advancements.

CONCLUSIONS

Included studies demonstrated the wide variety of ways in which data linkage can contribute to the public health response to child maltreatment. However, how research using linked data can be translated into effective service development and monitoring, or targeting of interventions, is underexplored in terms of privacy protection, ethics and governance, data quality, and evidence of effectiveness.

Complex early childhood experiences: Characteristics of Northern Territory children across health, education and child protection data

Early identification of vulnerable children to protect them from harm and support them in achieving their long-term potential is a community priority. This is particularly important in the Northern Territory (NT) of Australia, where Aboriginal children are about 40% of all children, and for whom the trauma and disadvantage experienced by Aboriginal Australians has ongoing intergenerational impacts. Given that shared social determinants influence child outcomes across the domains of health, education and welfare, there is growing interest in collaborative interventions that simultaneously respond to outcomes in all domains. There is increasing recognition that many children receive services from multiple NT government agencies, however there is limited understanding of the pattern and scale of overlap of these services. In this paper, NT health, education, child protection and perinatal datasets have been linked for the first time. The records of 8,267 children born in the NT in 2006-2009 were analysed using a person-centred analytic approach. Unsupervised machine learning techniques were used to discover clusters of NT children who experience different patterns of risk. Modelling revealed four or five distinct clusters including a cluster of children who are predominantly ill and experience some neglect, a cluster who predominantly experience abuse and a cluster who predominantly experience neglect. These three, high risk clusters all have low school attendance and together comprise 10-15% of the population. There is a large group of thriving children, with low health needs, high school attendance and low CPS contact. Finally, an unexpected cluster is a modestly sized group of non-attendees, mostly Aboriginal children, who have low school attendance but are otherwise thriving. The high risk groups experience vulnerability in all three domains of health, education and child protection, supporting the need for a flexible, rather than strictly differentiated response. Interagency cooperation would be valuable to provide a suitably collective and coordinated response for the most vulnerable children.

What Proportion of Foster Care Children Do Not Have Child Protective Services Reports? A Preliminary Look

It is perhaps surprising that we lack complete national information about why children enter foster care. While the annual Adoption and Foster Care Analysis Reporting System (AFCARS) report is informative, it leaves many questions unanswered, particularly "how many children enter foster care by means other than Child Protective Services (CPS) reports?" Drawing from a unique new integrated dataset, we examined foster care data (AFCARS) and CPS report data (National Child Abuse and Neglect Data System Child File). The linked dataset included 210,062 children with foster care placements in 2017 and no placements in the prior 5 years. We categorized each placed child along two dimensions of four levels each: Time since prior CPS report (if any) and stated AFCARS placement reason, ranging from clearly maltreated to clearly not maltreated. We also tracked the siblings of placed children, to see if non-maltreated children entered care because of maltreated siblings. We find that between 8-35% of children enter foster care for reasons other than maltreatment, depending how thresholds are set. These numbers decline somewhat when siblings are considered. A meaningfully large number of children are placed in foster care for reasons other than maltreatment investigated by CPS. Further research into these children is warranted to better inform foster care policy.

Mental illness concordance between hospital clinical records and mentions in domestic violence police narratives: Data linkage study (Preprint)

Background

To better understand domestic violence, data sources from multiple sectors such as police, justice, health, and welfare are needed. Linking police data to data collections from other agencies could provide unique insights and promote an all-of-government response to domestic violence. The New South Wales Police Force attends domestic violence events and records information in the form of both structured data and a free-text narrative, with the latter shown to be a rich source of information on the mental health status of persons of interest (POIs) and victims, abuse types, and sustained injuries.

Objective

This study aims to examine the concordance (ie, matching) between mental illness mentions extracted from the police’s event narratives and mental health diagnoses from hospital and emergency department records.

Methods

We applied a rule-based text mining method on 416,441 domestic violence police event narratives between December 2005 and January 2016 to identify mental illness mentions for POIs and victims. Using different window periods (1, 3, 6, and 12 months) before and after a domestic violence event, we linked the extracted mental illness mentions of victims and POIs to clinical records from the Emergency Department Data Collection and the Admitted Patient Data Collection in New South Wales, Australia using a unique identifier for each individual in the same cohort.

Results

Using a 2-year window period (ie, 12 months before and after the domestic violence event), less than 1% (3020/416,441, 0.73%) of events had a mental illness mention and also a corresponding hospital record. About 16% of domestic violence events for both POIs (382/2395, 15.95%) and victims (101/631, 16.01%) had an agreement between hospital records and police narrative mentions of mental illness. A total of 51,025/416,441 (12.25%) events for POIs and 14,802/416,441 (3.55%) events for victims had mental illness mentions in their narratives but no hospital record. Only 841 events for POIs and 919 events for victims had a documented hospital record within 48 hours of the domestic violence event.

Conclusions

Our findings suggest that current surveillance systems used to report on domestic violence may be enhanced by accessing rich information (ie, mental illness) contained in police text narratives, made available for both POIs and victims through the application of text mining. Additional insights can be gained by linkage to other health and welfare data collections.

Dual-system Involvement: Exploring the Overlap Between Domestic and Family Violence and Child Maltreatment Perpetration

This longitudinal population-based study aimed to understand the dual-system involvement of males who engage in domestic and family violence (DFV) and child maltreatment perpetration. Specifically, this study investigates the prevalence of male perpetration of DFV, child maltreatment, and dual-system involvement, and compares the frequency and nature of perpetration by males with single-system contact and males with dual-system contact. The effect of race (Indigenous Australian/non-Indigenous Australian) and parental status on dual-system involvement is also examined. This study utilizes data from the Queensland Cross-sector Research Collaboration repository. These data contain each contact an individual male born in 1983 or 1984 had with the Queensland civil court system as a respondent to a domestic violence order (DVO) and the Queensland statutory child protection system, where, after an investigation, they were identified as the person responsible for substantiated harm to a child. The results from the study show a high level of overlap between males who perpetrate DFV and child maltreatment. Of males identified as being responsible for substantiated harm to a child, 58% have also been a respondent of a DVO, and approximately 16% of male DVO respondents were identified as being responsible for substantiated harm to a child. Differences were found in the frequency and nature of perpetration by males with dual-system involvement compared to those with single-system contact for either DFV or child maltreatment. Our results also show differences for Indigenous status, parental status, number of maltreatment events, harm type, number of DVOs, and number of breaches of a DVO. The implications of this study for both policy and practice are discussed.

Exploring dual-system involvement for domestic violence victimisation and child maltreatment perpetration: An exploration by gender and race/ethnicity

BACKGROUND

There is an historical separation between system responses to domestic violence (DV) and child maltreatment. Concerns have been noted that DV victims may be over-represented as parents responsible for harm to children in the child protection system. Although there is a growing acknowledgement of the high overlap between DV and child maltreatment within families, little empirical research has been conducted on this relationship.

OBJECTIVE

This study aims to longitudinally examine the overlap of being a victim of DV and a perpetrator of child maltreatment, along with the impact of dual-system involvement on the nature and frequency of the violence experienced.

METHODS

The data are linked longitudinal administrative data from the Queensland Cross-sector Research Collaboration (QCRC) repository. These data contain each contact every individual born in Queensland in 1983 or 1984 had with the Queensland DV civil court system and the Queensland statutory child protection system.

RESULTS

Of individuals identified as a perpetrator of child maltreatment, 45% have also been a victim of DV and approximately 22% of DV victims were identified as a perpetrator of child maltreatment. Our results also show differences based on Indigenous status, gender, parental status, number of substantiations, frequency of violence, harm type, and number of domestic violence orders.

CONCLUSIONS

There is considerable overlap between individuals who are victims of DV and individuals who perpetrate child maltreatment. This overlap was influenced by both gender and race/ethnicity. The implications of this study for both policy and practice are discussed.

Utilising data linkage to describe and explore mortality among a retrospective cohort of individuals admitted to residential substance use treatment

INTRODUCTION

Individuals with moderate to severe substance use disorders may seek residential treatment, but outcomes after discharge for this hard-to-reach population are often unknown. Using linked data, we examined mortality outcomes among individuals after residential treatment.

METHODS

We included 1056 individuals admitted to three residential treatment facilities across Queensland, Australia, from 1 January 2014 to 31 December 2016. Records were linked to Queensland death registration data and cause of death records from the Australian Coordinating Registry (1 January-31 December 2018). Standard mortality ratios were assessed, comparing participants to the Queensland, Australia, general population. Causes of death and years of potential life lost (YPLL) were examined.

RESULTS

Thirty-six participants died (3.4%) in 3408 years of follow-up data. The age- and sex-adjusted standard mortality ratios were 3.96 (95% confidence interval: 2.78, 5.48) overall, 8.19 (3.74, 15.55) in females and 3.38 (2.23, 4.92) in males. Two-thirds of deaths were due to suicide/overdose. There was an average of 45.50 YPLL (SD 9.16).

DISCUSSION AND CONCLUSIONS

This study used linked data to quantify mortality following residential substance use treatment. The YPLL and avoidable nature of deaths highlight the need for continuing care following discharge from residential services.

Child maltreatment data: A summary of progress, prospects and challenges

BACKGROUND

In 1996, the ISPCAN Working Group on Child Maltreatment Data (ISPCAN-WGCMD) was established to provide an international forum in which individuals, who deal with child maltreatment data in their respective professional roles, can share concerns and solutions.

OBJECTIVE

This commentary describes some of the key features and the status of child maltreatment related data collection addressed by the ISPCAN-WGCMD.

METHODS

Different types of data collection methods including self-report, sentinel, and administrative data designs are described as well as how they address different needs for information to help understand child maltreatment and systems of prevention and intervention.

RESULTS

While still lacking in many parts of the world, access to child maltreatment data has become much more widespread, and in many places a very sophisticated undertaking.

CONCLUSION

The ISPCAN-WGCMD has been an important forum for supporting the continued development and improvement in the global effort to understand and combat child maltreatment thus contributing to the long term goals of the UN Convention on the Rights of the Child. Nevertheless, based on what has been learned, even greater efforts are required to improve data in order to effectively combat child maltreatment.

Research using population-based administration data integrated with longitudinal data in child protection settings: A systematic review

INTRODUCTION

Over the past decade there has been a marked growth in the use of linked population administrative data for child protection research. This is the first systematic review of studies to report on research design and statistical methods used where population-based administrative data is integrated with longitudinal data in child protection settings.

METHODS

The systematic review was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. The electronic databases Medline (Ovid), PsycINFO, Embase, ERIC, and CINAHL were systematically searched in November 2019 to identify all the relevant studies. The protocol for this review was registered and published with Open Science Framework (Registration DOI: 10.17605/OSF.IO/96PX8).

RESULTS

The review identified 30 studies reporting on child maltreatment, mental health, drug and alcohol abuse and education. The quality of almost all studies was strong, however the studies rated poorly on the reporting of data linkage methods. The statistical analysis methods described failed to take into account mediating factors which may have an indirect effect on the outcomes of interest and there was lack of utilisation of multi-level analysis.

CONCLUSION

We recommend reporting of data linkage processes through following recommended and standardised data linkage processes, which can be achieved through greater co-ordination among data providers and researchers.

Relationship between Child Sexual Abuse, Psychiatric Disorders and Infectious Diseases: A Matched-Cohort Study

Child sexual abuse (CSA) has been strongly associated with a range of psychological and physical problems in childhood and adulthood, such as anxiety, post-traumatic stress disorder (PTSD), and infectious diseases. Despite the strength of these associations, no studies to date have investigated psychobiological processes that might underlie the relationship between CSA and physical health problems occurring during childhood, such as infectious diseases. The goal of the current study is to evaluate PTSD as a potential mediator between CSA and the occurrence of infectious diseases among children and adolescents. Furthermore, we postulate that PTSD plays a specific role as an indicator of chronic stress during childhood, in comparison to other mental disorders, such as anxious and non-anxious disorders (e.g., depression). Via a prospective matched-cohort design, administrative data were used to document PTSD, anxious and non-anxious disorders, and infectious diseases. The sample size was 882 persons with a substantiated report of sexual abuse and 882 matched controls. Negative binomial regressions revealed that CSA is associated with a greater number of anxious diseases diagnoses that, in turn, predict more infectious diseases diagnoses. These findings highlight the importance of preventing and intervening among sexually abused youth with anxious disorder symptoms to limit negative outcomes on physical health.

Hospitalizations among children involved in the child protection system: A long-term birth cohort study from infancy to adulthood using administrative data

BACKGROUND

Despite considerable health consequences of child abuse and neglect, there is limited evidence on hospitalizations in this population.

OBJECTIVES

To describe frequency and reasons for hospitalization by lifetime child protection system (CPS) involvement.

PARTICIPANTS

608,540 children born from January 1, 1986 to June 30, 2017 in South Australia, Australia METHODS: Using linked administrative data on CPS involvement and hospitalizations, we descriptively examined cumulative incidence, cumulative count and reasons for hospitalization from infancy to early adulthood by CPS involvement.

RESULTS

By 16.5 years of age, cumulative incidence of ever-being hospitalized was 58% (95% CI 58-58) for children with no CPS involvement and significantly higher (72% (95% CI 71-73) to 88% (95% CI 86-90), P < 0.001) among those with different levels of CPS involvement. Cumulative mean counts of hospitalizations were highest at every age for those placed in out-of-home-care (reaching 7.7 by 16.5 years), almost four times higher than for children with no CPS involvement (2.0 by 16.5 years). Most frequent reasons for hospitalizations were similar across CPS involvement in the early years. From adolescence through early adulthood, mental health, and 'injury, poisoning or toxic effects of drugs' were frequent reasons for hospitalization among individuals with CPS involvement.

CONCLUSIONS

This study highlights the vulnerability of children who have been maltreated, or are at risk of maltreatment, and the urgency of implementing effective preventive strategies early in life including consideration of adequate responses of child protection services. Frequent hospitalizations for mental health and injury confirms the potentially preventable nature of these hospitalizations.

Long-term healthcare utilisation following child sex abuse: A follow-up study utilising five years of medical data

BACKGROUND

Limited attention has been paid to the long-term physical health consequences experienced by CSA survivors. Research has found that CSA is often associated with increased health burden in adulthood. However, research in this area is plagued by a range of methodological difficulties, rendering it difficult to draw conclusions regarding the health status of CSA survivors.

OBJECTIVE

This research sought to investigate associations between child sexual abuse (CSA) victimisation and rates of subsequent healthcare utilisation.

METHOD

The forensic medical records of 2759 cases of CSA between 1964 and 1995 were linked to commonwealth Australian medical data recorded between 2010 and 2015. Differences in rates of health service utilisation during this five-year period were compared between CSA victims and a age and gender matched comparison cohort without known abuse history.

FINDINGS

CSA was associated with increased levels of attendance at health professionals (OR = 1.51, p < .001) for medical care and for consultations related to dental (OR = 1.28, p < .001) and chronic disease (OR = 1.23, p <.001). CSA was associated with lower mean rates of attendance at gynaecologists. Gender and age at abuse significantly influenced the relationship between CSA and frequency of health service utilisation.

CONCLUSIONS

Experiencing CSA was associated with increases in rates of contact with health professionals. Abused females and victims abused after 12 years of age demonstrated the greatest elevations in rates of service utilisation. These findings have significance for both researchers in this field, and medical practitioners providing primary care.

Measuring the Incidence of Child Maltreatment Using Linked Data: A Two-State Comparison

INTRODUCTION

Measuring and comparing the incidence of child maltreatment is challenging. Linkage of statewide birth cohorts with Child Protective Services reports to study incident child maltreatment over the life course are becoming more common. This study compares the reported incidence between 2 states derived from population-based administrative data linkages.

METHODS

Linked births (2009-2011) with Child Protective Services records (2009-2015) and deaths in each state were used to compare the cumulative incidence of a Child Protective Services report before age 7 years. Given differences in population race structure and documented disparities of race groups in Child Protective Services data, variation was adjusted for using direct standardization. Unadjusted cumulative incidence, race cumulative incidence, and race-adjusted cumulative incidence were compared. Analyses were completed in 2018.

RESULTS

Before age 7 years, 26.0% of Alaskan children and 19.0% of Californian children were reported to Child Protective Services (RR=1.37, p<0.001). Aside from Asian/Pacific Islanders, the cumulative incidence between states was similar for each race. The race-adjusted cumulative incidence indicated that children born in Alaska were 1.10 times as likely to experience a report before age 7 years compared with children in California.

CONCLUSIONS

Much of the difference in risk for child maltreatment observed between Alaska and California is most likely due to variation in the population structure by race as opposed to modifiable factors. Standardization is a simple method to adjust for population structure differences. This study contributes to the growing body of knowledge regarding the use of linked administrative data to study maltreatment and provides insights into considerations for making comparisons or conducting cross-jurisdictional analyses based on commonly aligned data sets.

A Matched Cohort Study of the Association Between Childhood Sexual Abuse and Teenage Pregnancy

PURPOSE

This matched cohort study aims to determine whether teenagers with a history of childhood sexual abuse (CSA) are at greater risk of consulting for a pregnancy and related complications than teenagers from the general population. It also aims to compare provoked abortion, live births, and fetal losses of participants who were sexually abused in childhood and those of the general population.

METHODS

A total of 661 girls (aged 13-18 years) with a corroborated by Child Protection Services CSA report between 2001 and 2010 were matched to 661 girls from the general population upon age, biological sex, urban Child Protection Services area, and public drug insurance admissibility at reporting date. Pregnancy consultations and complications during pregnancy and delivery were documented using diagnoses from public health insurance administrative databases from January 1996 to March 2013. Socioeconomic status was controlled.

RESULTS

Results indicate that compared with participants from the general population, those with a history of CSA were 4.6 times more likely to consult for at least one pregnancy, 5.3 times more likely to consult for at least one complication during pregnancy or delivery, and on average 5.2 and 3.3 times more likely to consult for at least one live birth and provoked abortion, respectively. There were too few observations to compare fetal losses between groups.

CONCLUSIONS

Medical interventions for teenage pregnancies and related complications should take into consideration a possible history of CSA to reinforce gynecological follow-up and treatment for girls who were sexually abused and to prevent unfavorable outcomes.

An evaluation of welfare and child welfare system integration on rates of child maltreatment in Colorado

Policies that improve the socioeconomic conditions of families have been identified as one of the most promising strategies to prevent child maltreatment, particularly neglect. In this study, we examined the impact of integrated Temporary Assistance for Needy Families (TANF) and child welfare (CW) systems on child maltreatment-related hospitalizations and Child Protective Services investigations and substantiations in nine counties in Colorado from 1996 to 2014. Regression analyses showed TANF-CW integration was associated with subsequent year, but not second-year, increases rates of substantiated child maltreatment overall and neglect specifically (that is, there was no longer a difference in the rate two years after the change in integration). Neither unemployment nor the one- or two-year lagged effect of integration were significant for investigations or child maltreatment-related hospitalizations. Increased opportunities to interact with a family in crisis using an integrated case management model may help explain these findings. Implications for future research are discussed.

Linking Healthcare and Social Service Databases to Study the Epidemiology of Child Maltreatment and Associated Health Problems: Hong Kong's Experience

OBJECTIVE

To examine the incidence and trend of child maltreatment and its associated health problems in Hong Kong by linking healthcare and social service databases.

STUDY DESIGN

Data on 4816 children under the age of 18 years registered with the Child Protection Registry and matching health records in public hospitals in Hong Kong from 2003 to 2010 were extracted. Associations were examined between different types of child maltreatment and child's medical diagnosis according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision codes including suicidal attempt (X60-X84), nonchild maltreatment related injuries (S00-S99; T00-T98, excluding T74 and T76 that are maltreatment related injuries), mental health problems (F00-F99), and congenital malformations/chromosomal abnormalities (Q00-Q99).

RESULTS

Significant rising trends were found for child physical abuse, neglect, and sexual abuse during the period from 2003 to 2010. Psychological abuse remained stable. Risk of suicide attempt was higher among children suffering from sexual abuse, psychological abuse, and children experiencing multiple abuses; mental health diagnoses were more common in victims of psychological and multiple abuses. Congenital malformations and chromosomal abnormalities were more commonly found among neglected children.

CONCLUSIONS

In contrast to the decreasing trend observed in the West during the study period, there has been an escalating trend in child maltreatment in Hong Kong and child maltreatment is strongly associated with major health problems. This is one of the first studies to demonstrate the power of linking healthcare and social service databases, which allows for both a better understanding of the impact of child maltreatment and as a guide future policy and service planning.

Child Sexual Abuse and Criminal Offending: Gender-Specific Effects and the Role of Abuse Characteristics and Other Adverse Outcomes

This study sought to enhance knowledge of the link between child sexual abuse (CSA) and long-term criminality by investigating gender-specific effects and the role of index sexual abuse characteristics, revictimization, and serious mental health problems. An Australian sample of 2,759 documented cases of sexual abuse and 2,677 community controls were linked to statewide police records and public mental health service databases, with a follow-up period of 13-44 years. Four key findings emerged from the analysis: (1) CSA victims were more likely than controls to engage in all types of criminal behaviors including violent, sexual, and other offending; (2) gender moderated the relationship between CSA and criminal offending, with stronger associations found among females for general and violent offending, and among males for sexual offending; (3) certain features of the index sexual abuse (i.e., developmental period, number of perpetrators, relation to perpetrator), further victimization experiences, and the development of serious mental health problems were all associated with an increased likelihood of criminal behavior among CSA victims; (4) CSA victims who engaged in criminal offending were more likely to present with cumulative risks than victims not engaging in criminal offending. Implications for future research and clinical practice are discussed.

How well does the minimum data set measure healthcare use? a validation study

Background

To improve care, planners require accurate information about nursing home (NH) residents and their healthcare use. We evaluated how accurately measures of resident user status and healthcare use were captured in the Minimum Data Set (MDS) versus administrative data.

Methods

This retrospective observational cohort study was conducted on all NH residents (N = 8832) from Winnipeg, Manitoba, Canada, between April 1, 2011 and March 31, 2013. Six study measures exist. NH user status (newly admitted NH residents, those who transferred from one NH to another, and those who died) was measured using both MDS and administrative data. Rates of in-patient hospitalizations, emergency department (ED) visits without subsequent hospitalization, and physician examinations were also measured in each data source. We calculated the sensitivity, specificity, positive and negative predictive values (PPV, NPV), and overall agreement (kappa, κ) of each measure as captured by MDS using administrative data as the reference source. Also for each measure, logistic regression tested if the level of disagreement between data systems was associated with resident age and sex plus NH owner-operator status.

Results

MDS accurately identified newly admitted residents (κ = 0.97), those who transferred between NHs (κ = 0.90), and those who died (κ = 0.95). Measures of healthcare use were captured less accurately by MDS, with high levels of both under-reporting and false positives (e.g., for in-patient hospitalizations sensitivity = 0.58, PPV = 0.45), and moderate overall agreement levels (e.g., κ = 0.39 for ED visits). Disagreement was sometimes greater for younger males, and for residents living in for-profit NHs.

Conclusions

MDS can be used as a stand-alone tool to accurately capture basic measures of NH use (admission, transfer, and death), and by proxy NH length of stay. As compared to administrative data, MDS does not accurately capture NH resident healthcare use. Research investigating these and other healthcare transitions by NH residents requires a combination of the MDS and administrative data systems.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3089-7) contains supplementary material, which is available to authorized users.

Injury and Mortality Among Children Identified as at High Risk of Maltreatment

OBJECTIVES

To determine if children identified by a predictive risk model as at "high risk" of maltreatment are also at elevated risk of injury and mortality in early childhood.

METHODS

We built a model that predicted a child's risk of a substantiated finding of maltreatment by child protective services for children born in New Zealand in 2010. We assigned risk scores to the 2011 birth cohort, and flagged children as "very high risk" if they were in the top 10% of the score distribution for maltreatment. We also set a less conservative threshold for defining "high risk" and examined children in the top 20%. We then compared the incidence of injury and mortality rates between very high-risk and high-risk children and the remainder of the birth cohort.

RESULTS

Children flagged at both 10% and 20% risk thresholds had much higher postneonatal mortality rates than other children (4.8 times and 4.2 times greater, respectively), as well as a greater relative risk of hospitalization (2 times higher and 1.8 times higher, respectively).

CONCLUSIONS

Models that predict risk of maltreatment as defined by child protective services substantiation also identify children who are at heightened risk of injury and mortality outcomes. If deployed at birth, these models could help medical providers identify children in families who would benefit from more intensive supports.

Visualizing and Describing Foster Care Placement Pathways

This paper introduces a flowchart-based methodology for describing the movement of foster youth in and out of placements of differing types and durations. This longitudinal methodology is designed to be sufficiently simple to appeal to policymakers and administrators seeking to chart the movement of groups of youth over time and the sequencing of their placements, and sufficiently descriptive to be of use to researchers seeking to predict the placement trajectories of subgroups of foster youth. The paper provides an example of the use of the method drawing upon state administrative data from a large study of preadolescent and adolescent youth in foster care situated in Oregon. Implications for the application of the methodology to different issues of interest to researchers, policymakers, and administrators are discussed.

New Methods to Address Old Challenges: The Use of Administrative Data for Longitudinal Replication Studies of Child Maltreatment

Administrative data are crucial to the “big data” revolution of social science and have played an important role in the development of child maltreatment research. These data are also of value to administrators, policy makers, and clinicians. The focus of this paper is the use of administrative data to produce and replicate longitudinal studies of child maltreatment. Child protection administrative data have several advantages. They are often population-based, and allow longitudinal examination of child maltreatment and complex multi-level analyses. They also allow comparison across subgroups and minority groups, remove burden from individuals to disclose traumatic experiences, and can be less biased than retrospective recall. Finally, they can be linked to data from other agencies to explore comorbidity and outcomes, and are comparatively cost and time effective. The benefits and challenges associated with the use of administrative data for longitudinal child maltreatment research become magnified when these data are used to produce replications. Techniques to address challenges and support future replication efforts include developing a biographical understanding of the systems from which the data are drawn, using multiple data sources to contextualize the data and research results, recognizing and adopting various approaches to replication, and documenting all data coding and manipulation processes. These techniques are illustrated in this paper via a case study of previous replication work.

Quantifying sources of bias in longitudinal data linkage studies of child abuse and neglect: measuring impact of outcome specification, linkage error, and partial cohort follow-up

Background

Health informatics projects combining statewide birth populations with child welfare records have emerged as a valuable approach to conducting longitudinal research of child maltreatment. The potential bias resulting from linkage misspecification, partial cohort follow-up, and outcome misclassification in these studies has been largely unexplored. This study integrated epidemiological survey and novel administrative data sources to establish the Alaska Longitudinal Child Abuse and Neglect Linkage (ALCANLink) project. Using these data we evaluated and quantified the impact of non-linkage misspecification and single source maltreatment ascertainment use on reported maltreatment risk and effect estimates.

Methods

The ALCANLink project integrates the 2009–2011 Alaska Pregnancy Risk Assessment Monitoring System (PRAMS) sample with multiple administrative databases through 2014, including one novel administrative source to track out-of-state emigration. For this project we limited our analysis to the 2009 PRAMS sample. We report on the impact of linkage quality, cohort follow-up, and multisource outcome ascertainment on the incidence proportion of reported maltreatment before age 6 and hazard ratios of selected characteristics that are often available in birth cohort linkage studies of maltreatment.

Results

Failure to account for out-of-state emigration biased the incidence proportion by 12% (from 28.3%_w to 25.2%_w), and the hazard ratio (HR) by as much as 33% for some risk factors. Overly restrictive linkage parameters biased the incidence proportion downwards by 43% and the HR by as much as 27% for some factors. Multi-source linkages, on the other hand, were of little benefit for improving reported maltreatment ascertainment.

Conclusion

Using the ALCANLink data which included a novel administrative data source, we were able to observe and quantify bias to both the incidence proportion and HR in a birth cohort linkage study of reported child maltreatment. Failure to account for out-of-state emigration and low-quality linkage methods may induce bias in longitudinal data linkage studies of child maltreatment which other researchers should be aware of. In this study multi-agency linkage did not lead to substantial increased detection of reported maltreatment. The ALCANLink methodology may be a practical approach for other states interested in developing longitudinal birth cohort linkage studies of maltreatment that requires limited resources to implement, provides comprehensive data elements, and can facilitate comparability between studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s40621-017-0119-6) contains supplementary material, which is available to authorized users.

Linking routinely collected social work, education and health data to enable monitoring of the health and health care of school-aged children in state care ('looked after children') in Scotland: a national demonstration project

BACKGROUND AND OBJECTIVES

Children in state care ('looked after children') have poorer health than children who are not looked after. Recent developments in Scotland and elsewhere have aimed to improve services and outcomes for looked after children. Routine monitoring of the health outcomes of looked after children compared to those of their non-looked after peers is currently lacking. Developing capacity for comparative monitoring of population-based outcomes based on linkage of routinely collected administrative data has been identified as a priority. To our knowledge there are no existing population-based data linkage studies providing data on the health of looked after and non-looked after children at national level. Smaller scale studies that are available generally provide very limited information on linkage methods and hence do not allow scrutiny of bias that may be introduced through the linkage process.

STUDY DESIGN AND METHODS

National demonstration project testing the feasibility of linking routinely collected looked after children, education and health data.

PARTICIPANTS

All children in publicly funded school in Scotland in 2011/12.

RESULTS

Linkage between looked after children data and the national pupil census classified 10,009 (1.5%) and 1757 (0.3%) of 670,952 children as, respectively, currently and previously looked after. Recording of the unique pupil identifier (Scottish Candidate Number, SCN) on looked after children returns is incomplete, with 66% of looked after records for 2011/12 for children of possible school age containing a valid SCN. This will have resulted in some under-ascertainment of currently and, particularly, previously looked after children within the general pupil population. Further linkage of the pupil census to the National Health Service Scotland master patient index demonstrated that a safe link to the child's unique health service (Community Health Index) number could be obtained for a very high proportion of children in each group (94%, 95% and 95% of children classified as currently, previously, and non-looked after, respectively). In general, linkage rates were higher for older children and those living in more affluent areas. Within the looked after group, linkage rates were highest for children with the fewest placements and for those in permanent fostering.

CONCLUSIONS

This novel data linkage demonstrates the feasibility of monitoring population-based health outcomes of school-aged looked after and non-looked after children using linked routine administrative data. Improved recording of the unique pupil identifier number on looked after data returns would be beneficial. Extending the range of personal identifiers on looked after children returns would enable linkage to health data for looked after children who are not in publicly funded schooling (i.e. those who are preschool or postschool, home schooled or in independent schooling).

Exploring the longitudinal offending pathways of child sexual abuse victims: A preliminary analysis using latent variable modeling

Very little research has been conducted to show the way in which criminal behavior unfolds over the life-course in children who have been sexually abused, and whether it differs from the 'age-crime' patterns consistently documented in the criminology literature. This study investigated the temporal pathways of criminal offending between the ages of 10-25 years among medically confirmed cases of child sexual abuse (CSA), and considered whether abuse variables, offense variables, and the presence of other adverse outcomes, were associated with heterogeneity in offending pathways among CSA survivors. This study utilized data gathered as part of a large-scale study involving the linkage of forensic examinations on 2759 cases of medically ascertained CSA between 1964 and 1995, to criminal justice and public psychiatric databases 13-44 years following abuse, together with a matched comparison sample of 2677 individuals. We used the subsample of 283 offending individuals (191 victims; 92 comparisons) for whom complete offending data were available. We compared the aggregate age-crime curves for CSA victims and comparisons, and applied longitudinal latent class analysis to identify distinct subgroups of offending pathways between ages 10-25 years within the abuse sample. Four latent pathways emerged among sexually abused offenders, labeled: Early-Onset/High-Risk/Adolescence-Limited; Intermediate-Onset/Low-Risk/Adolescence-Limited; Late-Onset/Low-Risk/Slow-Declining; and Early-Onset/High-Risk/Persistent offenders. Age at abuse, the nature and frequency of offending, and mental health problems, were associated with the offending pathway followed by CSA victims. Consistent with criminological literature, findings indicate considerable heterogeneity in the longitudinal offending patterns of offenders exposed to CSA. Implications for clinical practice and directions for research are highlighted.

Physical and mental health of children with substantiated sexual abuse: Gender comparisons from a matched-control cohort study

When compared to children from the general population, sexually abused children receive more medical services, both for physical and mental health problems. However, possible differences between sexually abused boys and girls remain unknown. The lack of control group in studies that find gender differences also prevents from determining if the differences are specific to sexual abuse or to gender. The objective of the study was to assess differences in physical and mental health between sexually abused boys and girls in comparison to those from the general population. Administrative databases were used to document physical and mental health problems of 222 males and 660 females with a substantiated report of sexual abuse between 2001 and 2010. A comparison group individually matched to those from the sexually abused group on gender, age and geographic area was also used to document gender differences in the general population. Yearly incidence rates of diagnoses resulting from medical consultations and hospitalizations of males and females were compared over five years after a first substantiated sexual abuse report using the mixed general linear model. Sexually abused girls were up to 2.2 times more likely to consult a physician than sexually abused boys for physical health problems. Similar findings are observed in the general population. Conversely, results revealed that sexually abused boys were up to 2.3 times more likely than females to consult a physician for mental health problems. This gender difference was not apparent in the general population group.

Transitions and turning points revisited: A replication to explore child maltreatment and youth offending links within and across Australian cohorts

In this study we examined the consistency of life-course child maltreatment trajectories and youth offending links across birth cohorts. In so doing we demonstrated the value of replication studies for maltreatment research. We applied the methodology of Stewart et al. (2008) and linked population-based (1990 birth cohort) child protection and youth justice administrative data from Queensland, Australia. We performed a group based trajectory analysis to identify distinct maltreatment trajectory groups distinguishable by maltreatment timing and frequency across the life-course. We explored group-based youth offending outcomes with consideration of variations in maltreatment chronicity, timing, and frequency, multi-type maltreatment, gender and race (Indigenous Australian versus non-Indigenous Australian youths). To determine the consistency of maltreatment trajectories and offending links across cohorts (1983/84 versus 1990) we compared our results with those of Stewart et al. (2008). Consistent with Stewart et al. (2008): (1) We identified six distinct maltreatment trajectory groups; (2) Trajectory groups characterised by chronic maltreatment and/or adolescent maltreatment had the largest proportion of young offenders; and (3) Maltreatment frequency commonly peaked at transition points. Extending beyond Stewart et al. (2008) we noted considerable overlap between maltreatment dimensions and a potential impact of race and multi-type maltreatment on maltreatment and offending links. We endorse replication studies as a valuable tool to advance child maltreatment policy and practice and recommend further research on interactions between maltreatment dimensions, gender, race, and youth offending.

Using linked administrative and disease-specific databases to study end-of-life care on a population level

BACKGROUND

The use of full-population databases is under-explored to study the use, quality and costs of end-of-life care. Using the case of Belgium, we explored: (1) which full-population databases provide valid information about end-of-life care, (2) what procedures are there to use these databases, and (3) what is needed to integrate separate databases.

METHODS

Technical and privacy-related aspects of linking and accessing Belgian administrative databases and disease registries were assessed in cooperation with the database administrators and privacy commission bodies. For all relevant databases, we followed procedures in cooperation with database administrators to link the databases and to access the data.

RESULTS

We identified several databases as fitting for end-of-life care research in Belgium: the InterMutualistic Agency's national registry of health care claims data, the Belgian Cancer Registry including data on incidence of cancer, and databases administrated by Statistics Belgium including data from the death certificate database, the socio-economic survey and fiscal data. To obtain access to the data, approval was required from all database administrators, supervisory bodies and two separate national privacy bodies. Two Trusted Third Parties linked the databases via a deterministic matching procedure using multiple encrypted social security numbers.

CONCLUSION

In this article we describe how various routinely collected population-level databases and disease registries can be accessed and linked to study patterns in the use, quality and costs of end-of-life care in the full population and in specific diagnostic groups.

Case file coding of child maltreatment: Methods, challenges, and innovations in a longitudinal project of youth in foster care

State social service agency case files are a common mechanism for obtaining information about a child's maltreatment history, yet these documents are often challenging for researchers to access, and then to process in a manner consistent with the requirements of social science research designs. Specifically, accessing and navigating case files is an extensive undertaking, and a task that many researchers have had to maneuver with little guidance. Even after the files are in hand and the research questions and relevant variables have been clarified, case file information about a child's maltreatment exposure can be idiosyncratic, vague, inconsistent, and incomplete, making coding such information into useful variables for statistical analyses difficult. The Modified Maltreatment Classification System (MMCS) is a popular tool used to guide the process, and though comprehensive, this coding system cannot cover all idiosyncrasies found in case files. It is not clear from the literature how researchers implement this system while accounting for issues outside of the purview of the MMCS or that arise during MMCS use. Finally, a large yet reliable file coding team is essential to the process, however, the literature lacks training guidelines and methods for establishing reliability between coders. In an effort to move the field toward a common approach, the purpose of the present discussion is to detail the process used by one large-scale study of child maltreatment, the Studying Pathways to Adjustment and Resilience in Kids (SPARK) project, a longitudinal study of resilience in youth in foster care. The article addresses each phase of case file coding, from accessing case files, to identifying how to measure constructs of interest, to dealing with exceptions to the coding system, to coding variables reliably, to training large teams of coders and monitoring for fidelity. Implications for a comprehensive and efficient approach to case file coding are discussed.

It's not as simple as it sounds: Problems and solutions in accessing and using administrative child welfare data for evaluating the impact of early childhood interventions

In recent years, there has been increasing interest in using administrative data collected by state child welfare agencies as a source of information for research and evaluation. The challenges of obtaining access to and using these data, however, have not been well documented. This study describes the processes used to access child welfare records in six different states and the approach to combining and using the information gathered to evaluate the impact of the Early Head Start program on children's involvement with the child welfare system from birth through age eleven. We provide "lessons learned" for researchers who are attempting to use this information, including being prepared for long delays in access to information, the need for deep understanding of how child welfare agencies record and code information, and for considerable data management work for translating agency records into analysis-ready datasets. While accessing and using this information is not easy, and the data have a number of limitations, we suggest that the benefits can outweigh the challenges and that these records can be a useful source of information for policy-relevant child welfare research.

Understanding Overrepresentation of Indigenous Children in Child Welfare Data: An Application of the Drake Risk and Bias Models

Child welfare data collected for administrative purposes are often used as a source of information for understanding the population impact of child abuse and neglect (CA/N). This study used administrative data linked at the individual level for a cohort of Aotearoa New Zealand (NZ) children to follow and extend a model developed by Drake et al. In this investigation, we aimed to build an understanding of the high representation of indigenous NZ children in administratively sourced measures of CA/N. Variation in rate ratios (RRs) within infant mortality and birth outcomes considered as possible proxies for actual CA/N RRs leaves open a range of interpretations. Our findings indicate that a more nuanced interpretation of the overrepresentation of indigenous children in administratively recorded maltreatment statistics is required. Rather than considering risk and bias as competing explanations, we suggest an acknowledgment of the impact of colonization and the existence of systemic bias generating increased risk as key drivers. As linked administrative data are increasingly used for research and evaluation, and considered for use in supporting decision making, there is a need for a deeper understanding of the drivers of administratively recorded CA/N in order to effectively address the needs of indigenous populations.

What factors contribute to positive early childhood health and development in Australian Aboriginal children? Protocol for a population-based cohort study using linked administrative data (The Seeding Success Study)

INTRODUCTION

Australian Aboriginal children are more likely than non-Aboriginal children to have developmental vulnerability at school entry that tracks through to poorer literacy and numeracy outcomes and multiple social and health disadvantages in later life. Empirical evidence identifying the key drivers of positive early childhood development in Aboriginal children, and supportive features of local communities and early childhood service provision, are lacking.

METHODS AND ANALYSIS

The study population will be identified via linkage of Australian Early Development Census data to perinatal and birth registration data sets. It will include an almost complete population of children who started their first year of full-time school in New South Wales (NSW), Australia, in 2009 and 2012. Early childhood health and development trajectories for these children will be constructed via linkage to a range of administrative data sets relating to birth outcomes, congenital conditions, hospital admissions, emergency department presentations, receipt of ambulatory mental healthcare services, use of general practitioner services, contact with child protection and out-of-home care services, receipt of income assistance and fact of death. Using multilevel modelling techniques, we will quantify the contributions of individual-level and area-level factors to variation in early childhood development outcomes in Aboriginal and non-Aboriginal children. Additionally, we will evaluate the impact of two government programmes that aim to address early childhood disadvantage, the NSW Aboriginal Maternal and Infant Health Service and the Brighter Futures Program. These evaluations will use propensity score matching methods and multilevel modelling.

ETHICS AND DISSEMINATION

Ethical approval has been obtained for this study. Dissemination mechanisms include engagement of stakeholders (including representatives from Aboriginal community controlled organisations, policy agencies, service providers) through a reference group, and writing of summary reports for policy and community audiences in parallel with scientific papers.

Predictive modeling: potential application in prevention services

INTRODUCTION

In 2012, the New Zealand Government announced a proposal to introduce predictive risk models (PRMs) to help professionals identify and assess children at risk of abuse or neglect as part of a preventive early intervention strategy, subject to further feasibility study and trialing. The purpose of this study is to examine technical feasibility and predictive validity of the proposal, focusing on a PRM that would draw on population-wide linked administrative data to identify newborn children who are at high priority for intensive preventive services.

METHODS

Data analysis was conducted in 2013 based on data collected in 2000-2012. A PRM was developed using data for children born in 2010 and externally validated for children born in 2007, examining outcomes to age 5 years.

RESULTS

Performance of the PRM in predicting administratively recorded substantiations of maltreatment was good compared to the performance of other tools reviewed in the literature, both overall, and for indigenous Māori children.

CONCLUSIONS

Some, but not all, of the children who go on to have recorded substantiations of maltreatment could be identified early using PRMs. PRMs should be considered as a potential complement to, rather than a replacement for, professional judgment. Trials are needed to establish whether risks can be mitigated and PRMs can make a positive contribution to frontline practice, engagement in preventive services, and outcomes for children. Deciding whether to proceed to trial requires balancing a range of considerations, including ethical and privacy risks and the risk of compounding surveillance bias.

Data research on child abuse and neglect without informed consent? Balancing interests under Dutch law

According to the Declaration of Helsinki, participation of human subjects in medical research is only acceptable if subjects have given their consent. But in child abuse and neglect, many studies use a design in which subjects do not actively participate. Data in these studies are gathered from sources such as medical records or Child Protective Services. As long as such data are used anonymously, this does not interfere with individual privacy rights. However, some research is only possible when carried out with personally identifiable data, which could potentially be misused. In this paper, we discuss in which situations and under which conditions personal data of children may be used for a study without obtaining consent. In doing so, we make use of two recent studies, performed in our hospital, in which we encountered this issue. Both studies involved collecting personal data. After careful consideration, we decided not to ask informed consent; instead, we arranged for specific safeguards to protect the subject's and their parents' privacy as well as possible.

CONCLUSION

Altogether, we conclude that our approach fits within the Dutch legal framework and seems a reasonable solution in situations in which individual privacy rights are at odds with the public interest of child abuse and neglect research. We argue that, although, in principle, data research is only acceptable after informed consent is obtained, the law should allow that, under specific circumstances and safeguards, this requirement is put aside to make research in the field of child abuse and neglect possible.

WHAT IS KNOWN

• In principle, data research is only acceptable after informed consent is obtained.• In practice, this is not always feasible.

WHAT IS NEW

• Under specific circumstances and safeguards, the informed consent requirement can be put aside.

Involvement with child protective services: is this a useful question in population-based surveys?

Direct questions on child maltreatment in population-based surveys are often limited by ethical and methodological issues. This restricts the ability of researchers to examine an important aspect of early adversity and its relationship to health and behavior. An alternative to excluding issues of maltreatment entirely in population-based surveys is to include questions on child and family involvement with child protective services (CPS). A school-based adolescent survey that included a question on child and family involvement with CPS yielded results that were generally consistent with other studies relating child maltreatment to health and behavioral outcomes such as psychological distress symptoms, delinquency, aspects of bullying, and health service utilization. Such findings suggest that questions on involvement with CPS may be a reasonable proxy for child maltreatment. Despite the lack of information on the reason for involvement or specific categories of maltreatment, CPS involvement questions highlight the shared familial experience that surrounds CPS involvement and serves as a general reflection of an adverse experience that can be utilized by researchers interested in early experiences.