Leveraging Administrative Data to Better Understand and Address Child Maltreatment: A Scoping Review of Data Linkage Studies
Year: 2022
Type: review
Study design: Systematic Review
Abstract: 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.
Source: Child Maltreatment
Language: English
Topic: Child Abuse and Trauma
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,250
Awards: Evaluating the real-world implementation of the Family Nurse Partnership: a data linkage study, NIHR Senior Investigator Award, G299057155, Enhancement of ECHILD with a mother-child and Unique Property Reference number link, FAIR TREATMENT: Federated analytics and AI Research across TREs for AdolescenT MENTal health
OpenAlex ID: W4214935634
