Evidence map›Paper›PMID 32133423›Full record

ArticleNPJ digital medicine2020

Tools and analytic techniques to synthesise community knowledge in CBPR using computer-mediated participatory system modelling.

Joshua Hayward, Saraya Morton, Michael Johnstone, Doug Creighton, Steven Allender

Abstract read
In one paragraph

Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
–field-weighted citation impact
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

39 citing papers in PubMed.

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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

5 authors.

Joshua Hayward1Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, 3220 Australia.ORCID 0000-0001-8484-9930
Saraya Morton1Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, 3220 Australia.
Michael Johnstone2Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, Australia.
Doug Creighton2Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, Australia.
Steven Allender1Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, 3220 Australia.ORCID 0000-0002-4842-3294

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Participatory systems thinking methods are often used in community-based participatory research to engage and respond to complexity. Participation in systems thinking activities creates opportunities for participants to gain useful insights about complexity. It is desirable to design activities that extend the benefits of this participation into communities, as these insights are predictive of success in community-based prevention. This study tests an online, computer-mediated participatory system modelling platform (STICKE) and associated methods for collating and analysing its outputs. STICKE was trialled among a group of community members to test a computer-mediated system modelling exercise. The causal diagrams resulting from the exercise were then merged, and network analysis and DEMATEL methods applied to inform the generation of a smaller summary model to communicate insights from the participant group as a whole. Participants successfully completed the online modelling activity, and created causal diagrams consistent with expectations. The DEMATEL analysis was identified as the participant-preferred method for converging individuals causal diagrams into a coherent and useful summary. STICKE is an accessible tool that enabled participants to create causal diagrams online. Methods trialled in this study provide a protocol for combining and summarising individual causal diagrams that was perceived to be useful by the participant group. STICKE supports communities to consider and respond to complex problems at a local level, which is cornerstone of sustainable effective prevention. Understanding how communities perceive their own health challenges will be important to better support and inform locally owned prevention efforts.

Indexed as

ObesitySociety

Identifiers

PMID32133423
PMCPMC7031223

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.