Evidence map›Paper›PMID 38504205›Full record

ArticleBMC public health2024

The common drivers of children and young people's health and wellbeing across 13 local government areas: a systems view.

Siobhan A O'Halloran, Joshua Hayward, Melissa Valdivia Cabrera, Tiana Felmingham, Penny Fraser, Cindy Needham, Jaimie Poorter, Doug Creighton, Michael Johnstone, Melanie Nichols and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Siobhan A O'HalloranGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia. s.ohalloran@deakin.edu.au.
Joshua HaywardGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Melissa Valdivia CabreraInstitute for Intelligent Systems Research and Innovation, Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC, 3216, Australia.
Tiana FelminghamGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Penny FraserGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Cindy NeedhamGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Jaimie PoorterGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Doug CreightonInstitute for Intelligent Systems Research and Innovation, Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC, 3216, Australia.
Michael JohnstoneInstitute for Intelligent Systems Research and Innovation, Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC, 3216, Australia.
Melanie NicholsGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Steven AllenderGlobal Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, 3220, Australia.
Deakin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSystem dynamics approaches, including group model building (GMB) and causal loop diagrams (CLDs), can be used to document complex public health problems from a community perspective. This paper aims to apply Social Network Analysis (SNA) methods to combine multiple CLDs created by local communities into a summary CLD, to identify common drivers of the health and wellbeing of children and young people.

methodsThirteen community CLDs regarding children and young people health and wellbeing were merged into one diagram involving three steps: (1) combining variable names; (2) CLD merging, where multiple CLDs were combined into one CLD with a set of unique variables and connections; (3) paring, where the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to generate a cut-point to reduce the number of variables and connections and to rank the overall importance of each variable in the merged CLD.

resultsCombining variable names resulted in 290 variables across the 13 CLDS. A total of 1,042 causal links were identified in the merged CLD. The DEMATEL analysis of the merged CLD identified 23 common variables with a net importance between 1.0 and 4.5 R + C values and 57 causal links. The variables with the highest net importance were 'mental health' and 'social connection & support' classified as high net receivers of influence within the system.

conclusionsCombining large CLDs into a simple diagram represents a generalisable model of the drivers of complex health problems.

Indexed as

Local GovernmentPublic HealthAdolescentChildHumansCommunityHealthLocal governmentSocial network analysisSystems thinking

Identifiers

PMID38504205
PMCPMC10949822
OpenAlexW4392960680

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.