Evidence map›Paper›PMID 35254646›Full record

SynthesisAmbio2022

The benefits of Q + PPGIS for coupled human-natural systems research: A systematic review.

Malcolm S Johnson, Vanessa M Adams, Jason Byrne, Rebecca M B Harris

Abstract readSystematic Review
In one paragraph

Synthesis in Ambio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

4 authors.

Malcolm S JohnsonSchool of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, TAS, 7000, Australia. malcolm.johnson@utas.edu.au.ORCID http://orcid.org/0000-0002-1187-071X
Vanessa M AdamsSchool of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, TAS, 7000, Australia.
Jason ByrneSchool of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, TAS, 7000, Australia.
Rebecca M B HarrisSchool of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, TAS, 7000, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Managing complex problems in socio-ecological systems (SES) requires innovative approaches, which account for multiple scales, large datasets, and diverse lived experiences. By combining two commonly utilized mixed-methods, public participation GIS (PPGIS) and Q-method (Q), Q + PPGIS has the potential to reveal competing agendas and reduce conflict, but its benefits and weaknesses are comparatively understudied. Using a systematic review, we evaluated how different studies have employed and implemented the Q + PPGIS method. We found 16 studies, comprising 30 publications, with considerable variation in their geographic foci, research disciplines, and addressed SES challenges. These studies exhibit a lack of cohesion between methodological design and implementation and the absence of a consistent application of the method. Nonetheless, Q + PPGIS offers a tool that can guide policy, better inform stakeholders, and reduce conflict based on misconceptions. Resolving the shortcomings identified here will broaden Q + PPGIS utility in geographically situating and representing multiple realities within complex socio-ecological systems challenges.

Indexed as

Community ParticipationGeographic Information SystemsEcosystemHumansEnvironmental managementMixed-methodPlanningPPGISQ-methodSocio-ecological system

Identifiers

PMID35254646
PMCPMC9200925

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.