ArticleInjury epidemiology2017
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.
Article in Injury epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Pooled it
- Risk and Protective Factors for Parental Involvement and Early Indicators of School Achievement in Alaska.Maternal and child health journal · 2024Article
- Leveraging Administrative Data to Better Understand and Address Child Maltreatment: A Scoping Review of Data Linkage Studies.Child maltreatment · 2023Article
- Pre-Birth Household Challenges Predict Future Child's School Readiness and Academic Achievement.Children (Basel, Switzerland) · 2022Article
- Patterns of Risk and Protective Factors Among Alaska Children: Association With Maternal and Child Well-Being.Child development · 2020Article
- Heterogeneity in Risk and Protection Among Alaska Native/American Indian and Non-Native Children.Prevention science : the official journal of the Society for Prevention Research · 2020Article
- Preconception and Prenatal Predictors of Early Experiences of Risk and Protection Among Alaska Children.Maternal and child health journal · 2020Article
- Trajectories of child protective services contact among Alaska Native/American Indian and non-Native children.Child abuse & neglect · 2019Article
- Survey evidence of the decline in child abuse in younger Canadian cohorts.European journal of pediatrics · 2019Article
- Assessment of Rates of Child Maltreatment in States With Medicaid Expansion vs States Without Medicaid Expansion.JAMA network open · 2019Observational
- Sociodemographic differences in linkage error: an examination of four large-scale datasets.BMC health services research · 2018Article
- A Longitudinal Study of Child Maltreatment and Mental Health Predictors of Admission to Psychiatric Residential Treatment Facilities.International journal of environmental research and public health · 2017Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundHealth 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.
methodsThe 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.
resultsFailure to account for out-of-state emigration biased the incidence proportion by 12% (from 28.3%
conclusionUsing 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.
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