Please use this identifier to cite or link to this item: https://anrows.intersearch.com.au/anrowsjspui/handle/1/16641
Record ID: b9a7a7cd-9fcc-4bcd-b52b-f37672be822a
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dc.contributor.authorO’Donnell, Melissaen
dc.contributor.authorFerrante, Annaen
dc.contributor.authorSpeyer, Reneeen
dc.contributor.authorChikwava, Fadzaien
dc.contributor.authorParsons, Laurenen
dc.contributor.authorCordier, Reinieen
dc.date.accessioned2022-06-30T23:27:23Z-
dc.date.available2022-06-30T23:27:23Z-
dc.date.issued2021en
dc.identifier.citationVolume 16, Issue 3en
dc.identifier.urihttps://anrows.intersearch.com.au/anrowsjspui/handle/1/16641-
dc.description.abstractIntroduction 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.en
dc.languageenen
dc.publisherPublic Library of Scienceen
dc.relation.ispartofPLoS ONEen
dc.titleResearch using population-based administration data integrated with longitudinal data in child protection settings: A systematic reviewen
dc.typeJournal Articleen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0249088en
dc.identifier.catalogid16901en
dc.subject.keywordnew_recorden
dc.subject.readinglistANROWS Notepad 2021 April 8en
dc.date.entered2021-04-01en
dc.subject.listANROWS Notepad 2021 April 8en
Appears in Collections:Journal Articles

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