bims-simosr 2026-03-15 papers

Issue of 2026–03–15
four papers selected by
Eunice T. Adwubi, University of Newcastle

Health Res Policy Syst. 2026 Mar 10.

Participatory systems mapping: a review of population health research practice.

Carolyn Blake, Benjamin P Rigby, Martin White, Kirstin R Mitchell, Sharon A Simpson, Nigel Gilbert, Roxanne Armstrong-Moore, Petra S Meier, Alexandra Penn, Mohammad Hassannezhad, Valerie Wells, Laurence Moore.

BACKGROUND: Participatory systems mapping (PSM) methods are increasingly applied in population health research to understand and address complex challenges. Despite their growing use, there remains limited understanding of how these approaches are implemented in practice. This systematic scoping review aimed to explore the application of PSM in population health research, identify methodological gaps and highlight opportunities for advancing methods development and reporting standards, with particular attention to participatory approaches.
METHODS: A systematic search of OVID MEDLINE and Scopus identified peer-reviewed papers published in English between January 2000 and September 2023 that: (1) applied and presented the results of PSM related to population health or health improvement questions and (2) incorporated a participatory design. Two reviewers screened and assessed papers, extracting data on study characteristics, participatory approaches, map features and integration of conceptual frameworks and methods not directly related to PSM.
RESULTS: In the 123 included studies, involving stakeholders in building causal loop diagrams was the most commonly used approach. Variability was evident in geographical focus, study design, application and reporting. Participant involvement was mostly limited to map building, with less engagement in map validation. Significant gaps in reporting study samples and procedures were identified. A small number of studies involved end users or people with lived experiences in mapping processes. Only a few studies evaluated stakeholders' experience with participatory processes. Lessons learnt on participatory processes include: PSM in population health benefits from cross-disciplinary, inclusive collaboration and capacity-building efforts that support meaningful involvement, shared ownership and trust among diverse stakeholders. Adaptability in the design of PSM approaches, continuous reflection and long-term partnerships are essential to maintaining relevance, enhancing impact and fostering systemic change over time.
CONCLUSIONS: To advance participatory systems mapping in population health, there is a need for further methodological innovation, stronger stakeholder engagement and more transparent, reflexive reporting practices. Building capacity through training, practical guidance and cross-disciplinary communities of practice will also be essential to support rigorous and inclusive application of these methods.

Keywords: Bayesian belief networks; CECAN PSM; Causal loop diagram; Fuzzy cognitive mapping; Involvement; Participatory systems mapping; Population health; System dynamics; Systems thinking; Systems-based theory of change

DOI: https://doi.org/10.1186/s12961-026-01457-6

Health Res Policy Syst. 2026 Mar 11.

Towards socially robust policy modelling: scoping review of public involvement in computational policy modelling.

Ellen Stewart, Natalie Dewison, Edit Gedeon, Clementine Hill-O'Connor.

Computational policy modelling appeals to policymakers seeking to understand potential outcomes of policy decisions, yet there are long-standing concerns about the "social robustness" of the knowledge it generates. A key route to socially robust policy modelling is the active involvement of publics as partners, and not only subjects, of modelling; yet the technical and abstracted nature of the modelling process poses particular challenges for conventional involvement practice. This scoping review of published computational modelling papers which report public involvement explores both practical elements of involvement in modelling and the tacit or explicit justifications authors offer for involving publics. We found a preponderance of professional stakeholders over "lay" publics and a bifurcation between informal feedback and highly structured input. We conclude that approaches to public involvement in computational policy modelling should seek ongoing dialogic involvement across the stages of the modelling process, be more attentive to power dynamics in the involvement process, and consider how involvement can be inclusive of diverse publics.

Keywords: Computational modelling; Public involvement; Socially robust research

DOI: https://doi.org/10.1186/s12961-026-01473-6

MethodsX. 2026 Jun;16 103820

An Agent-Based Model for Simulating Flood Governance and Community Resilience.

Anqi Zhu, Wenhan Feng, Huan Zheng, Yingxin Huang, Xin He, Chengying Zhou, Liang Emlyn Yang.

Agent-based modeling (ABM) is a unique tool for understanding social mechanisms and emergent phenomena. The paper presents an empirically grounded agent-based model that simulates how stakeholders embedded in flood governance networks facilitate community loss-sharing and post-flood recovery. The model is designed and calibrated using extensive empirical data from communities in Guangzhou, China. Modeled agents include multi-level government agencies, NGOs, private sector entities, and local clans, among others. The model integrates core processes (rainfall and flood impacts, network-based loss sharing and recovery, and the implementation of resilience measures) with modules for trust evolution and resource constraints. The purpose of this model is to evaluate the effects of different network structures, inter-stakeholder trust, and the diffusion of flood resilience measures on community flood resilience, and to advance the understanding of how resilience emerges as a macro-level attribute from micro-level interactions. Innovations are twofold: First, it moves beyond static analysis to simulate the dynamic, network-based collaborative processes among diverse institutional stakeholders; Second, it implements a process-based framework to measure community robustness and adaptivity, using these metrics to evaluate overall community resilience to floods. Key parameters, derived from literature and empirical research, were validated and tested via sensitivity analysis. The model serves as an accessible tool for researchers and practitioners interested in stakeholder collaborations in community-level climate governance and identifying optimal intervention strategies. • The model is described using the ODD protocol. • Validation, sensitivity analysis, and the number of minimum simulation runs are explained. • Complete NetLogo code and a brief user guide are provided.

Keywords: China; Community resilience; Emergency response; Flood resilience; Governance network; Post-disaster recovery; Social simulation

DOI: https://doi.org/10.1016/j.mex.2026.103820

PLoS One. 2026 ;21(3): e0344385

Quality assessment reporting checklists for microsimulation models: A scoping review protocol.

Claire de Oliveira.

BACKGROUND: Microsimulation models are computer-based models that can be used to understand how economic agents behave in different situations. These models are used by governments to help them make decisions. However, it is important these models are well built and produce useful information. Reporting checklists can help guide researchers confirm that all the necessary elements are included in a model. There are currently no formal reporting checklists to evaluate the quality of microsimulation models. This protocol aims to describe a scoping review, which will retrieve and synthesise the literature on any existing quality assessment checklists for microsimulation models and/or any literature that provides best practices, guidelines, and/or recommendations around which elements should be included.
METHODS: We will undertake a scoping review followed the PRISMA guidelines for Scoping Reviews. We will search MEDLINE, Embase, EconLit, and Web of Science, with an update closer to the time of manuscript submission. In addition, where relevant, we will undertake Google searches and searches on specific journals (e.g., International Journal of Microsimulation) and websites (e.g., https://www.microsimulation.ac.uk/) to complement the database searches. We will extract relevant data on quality dimensions and use a narrative synthesis to describe the recommendations.
DISCUSSION: There are no formal checklists to assess the quality of microsimulation models. Moreover, no scoping reviews have been undertaken on this topic. This work will synthesise any existing recommendations regarding the development of robust microsimulation models. A validated quality assessment reporting checklist will be the first of its kind and thus, fill an important gap in the literature.

DOI: https://doi.org/10.1371/journal.pone.0344385