Evidence map›Paper›PMID 40838187›Full record

ArticleCochrane evidence synthesis and methods2025

Optimizing Research Impact: A Toolkit for Stakeholder-Driven Prioritization of Systematic Review Topics.

Dyon Hoekstra, Stefan K Lhachimi

Abstract read
In one paragraph

Article in Cochrane evidence synthesis and methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Dyon HoekstraResearch Group for Evidence-Based Public Health, Leibniz-Institute for Prevention Research and Epidemiology (BIPS), Institute for Public Health and Nursing Research (IPP), University of Bremen Bremen Germany.ORCID https://orcid.org/0000-0003-0677-2063
Stefan K LhachimiResearch Group for Evidence-Based Public Health, Leibniz-Institute for Prevention Research and Epidemiology (BIPS), Institute for Public Health and Nursing Research (IPP), University of Bremen Bremen Germany.ORCID https://orcid.org/0000-0001-8597-0935

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intro: The prioritization of topics for evidence synthesis is crucial for maximizing the relevance and impact of systematic reviews. This article introduces a comprehensive toolkit designed to facilitate a structured, multi-step framework for engaging a broad spectrum of stakeholders in the prioritization process, ensuring the selection of topics that are both relevant and applicable. Methods: We detail an open-source framework comprising 11 coherent steps, segmented into scoping and Delphi stages, to offer a flexible and resource-efficient approach for stakeholder involvement in research priority setting. Results: The toolkit provides ready-to-use tools for the development, application, and analysis of the framework, including templates for online surveys developed with free open-source software, ensuring ease of replication and adaptation in various research fields. The framework supports the transparent and systematic development and assessment of systematic review topics, with a particular focus on stakeholder-refined assessment criteria. Conclusion: Our toolkit enhances the transparency and ease of the priority-setting process. Targeted primarily at organizations and research groups seeking to allocate resources for future research based on stakeholder needs, this toolkit stands as a valuable resource for informed decision-making in research prioritization.

Indexed as

Delphi techniquePICOpriority settingstakeholder involvementsystematic reviewtoolkit

Identifiers

PMID40838187
PMCPMC12362723

What OpenQuestion holds

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LicenceCC BY
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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.