Evidence map›Paper›PMID 32106861›Full record

ArticleBMC medical informatics and decision making2020

Case identification of mental health and related problems in children and young people using the New Zealand Integrated Data Infrastructure.

Nicholas Bowden, Sheree Gibb, Hiran Thabrew, Jesse Kokaua, Richard Audas, Sally Merry, Barry Taylor, Sarah E Hetrick

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
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  8. Identifying neurodevelopmental disabilities from nationalised preschool health check.The Australian and New Zealand journal of psychiatry · 2023
    Article
  9. Article
  10. Review
  11. Use of Population-Level Administrative Data in Developmental Science.Annual review of developmental psychology · 2022
    Article
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  13. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Nicholas BowdenA Better Start National Science Challenge, Auckland, New Zealand. Nick.Bowden@otago.ac.nz.ORCID 0000-0003-4589-9956
Sheree GibbA Better Start National Science Challenge, Auckland, New Zealand.
Hiran ThabrewA Better Start National Science Challenge, Auckland, New Zealand.
Jesse KokauaA Better Start National Science Challenge, Auckland, New Zealand.
Richard AudasA Better Start National Science Challenge, Auckland, New Zealand.
Sally MerryA Better Start National Science Challenge, Auckland, New Zealand.
Barry TaylorA Better Start National Science Challenge, Auckland, New Zealand.
Sarah E HetrickA Better Start National Science Challenge, Auckland, New Zealand.
University of Otago · NZUniversity of Auckland · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn a novel endeavour we aimed to develop a clinically relevant case identification method for use in research about the mental health of children and young people in New Zealand using the Integrated Data Infrastructure (IDI). The IDI is a linked individual-level database containing New Zealand government and survey microdata.

methodsWe drew on diagnostic and pharmaceutical information contained within five secondary care service use and medication dispensing datasets to identify probable cases of mental health and related problems. A systematic classification and refinement of codes, including restrictions by age, was undertaken to assign cases into 13 different mental health problem categories. This process was carried out by a panel of eight specialists covering a diverse range of mental health disciplines (a clinical psychologist, four child and adolescent psychiatrists and three academic researchers in child and adolescent mental health). The case identification method was applied to the New Zealand youth estimated resident population for the 2014/15 fiscal year.

resultsOver 82,000 unique individuals aged 0-24 with at least one specified mental health or related problem were identified using the case identification method for the 2014/15 fiscal year. The most prevalent mental health problem subgroups were emotional problems (31,266 individuals), substance problems (16,314), and disruptive behaviours (13,758). Overall, the pharmaceutical collection was the largest source of case identification data (59,862).

conclusionThis study demonstrates the value of utilising IDI data for mental health research. Although the method is yet to be fully validated, it moves beyond incidence rates based on single data sources, and provides directions for future use, including further linkage of data to the IDI.

Indexed as

Databases, FactualMental HealthAdolescentAdultChildChild, PreschoolData CollectionFemaleHumansInfantInfant, NewbornMaleMental DisordersNew ZealandPrevalenceYoung AdultAdministrative dataBig dataCase identificationIntegrated data infrastructureMental health

Identifiers

PMID32106861
PMCPMC7045433
OpenAlexW3012752926

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.