Evidence map›Paper›PMID 39681242›Full record

ArticleAnnals of epidemiology2025

Considerations for using participatory systems modeling as a tool for implementation mapping in chronic disease prevention.

Travis R Moore, Erin Hennessy, Yuilyn Chang Chusan, Laura Ellen Ashcraft, Christina D Economos

Abstract read
In one paragraph

Article in Annals of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

5 authors.

Travis R MooreChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States. Electronic address: travis.moore@tufts.edu.
Erin HennessyChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States.
Yuilyn Chang ChusanChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States.
Laura Ellen AshcraftDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, United States; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States; Penn Implementation Science Center (PISCE), University of Pennsylvania, Philadelphia, PA, United States.
Christina D EconomosChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States.

Funding

Feasibility of Network Interventions to Facilitate Community Coalition Adoption of Evidence-Based Strategies for Child Obesity PreventionK99HD109456 · NICHD · TUFTS UNIVERSITY BOSTON · PI MOORE, TRAVIS ROBERT · 2023 to 2024
$208k
NICHD NIH HHS K99 HD109456
6 · The paper itself

Abstract

Effective chronic disease prevention requires a systems approach to the design, implementation, and refinement of interventions that account for the complexity and interdependence of factors influencing health outcomes. This paper proposes the Participatory Implementation Systems Mapping (PISM) process, which combines participatory systems modeling with implementation strategy development to enhance intervention design and implementation planning. PISM leverages the collaborative efforts of researchers and community partners to analyze complex health systems, identify key determinants, and develop tailored interventions and strategies that are both adaptive and contextually relevant. The phases of the PISM process include strategize, innovate, operationalize, and assess. We describe and demonstrate how each phase contributes to the overall goal of effective and sustainable intervention implementation. We also address the challenges of data availability, model complexity, and resource constraints. We offer solutions such as innovative data collection methods and participatory model development to enhance the robustness and applicability of systems models. Through a case study on the development of a chronic disease prevention intervention, the paper illustrates the practical application of PISM and highlights its potential to guide epidemiologists and implementation scientists in developing interventions that are responsive to the complexities of real-world health systems. The conclusion calls for further research to refine participatory systems modeling techniques, overcome existing challenges in data availability, and expand the use of PISM in diverse public health contexts.

Indexed as

Community-Based Participatory ResearchChronic DiseaseHumansProgram DevelopmentSystems AnalysisCommunity-engaged researchEpidemiologyImplementation mappingImplementation scienceSystems scienceSystems thinking

Identifiers

PMID39681242
PMCPMC11728936

What OpenQuestion holds

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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.