bims-simosr 2026-03-29 papers

Issue of 2026–03–29
four papers selected by
Eunice T. Adwubi, University of Newcastle

J Hum Nutr Diet. 2026 Apr;39(2): e70234

Using Expert Elicitation and Systems Mapping to Support Social Innovation in the (Blue) Food System: The Case of the UK's Plymouth Fish Finger.

Pettinger Clare, Parsons Kelly, Irazu Yanaina Chavez-Ugalde, Hunt Louise, Wagstaff Carol.

BACKGROUND: The imperative for food system transformation is well known, yet to date there has been minimal emphasis on the blue food system [foods sourced from marine and freshwater environments]. Generally, a food systems approach should shift away from linear and move towards more systems thinking to embrace complexity. This paper focuses on a local social innovation project (Plymouth Fish Finger (PFF)) which has pioneered localising the blue food system. This study aimed to elicit how the (policy and practice) system around the PFF can be appraised to optimise social innovation practices for (blue) food system transformation.
METHODS: Expert elicitation combined with group model building (GMB) to co-create and validate a 'Causal Loop Diagram' (CLD) to visually understand the policy and practice implication and needs of the PFF initiative. Purposive sampling to recruit a range (n = 14 total) of experts representing the different parts of the system. Two 'mapping' workshops (one face-to-face, one online) facilitated elicitation of expert input into the process to enable establishment of a final synthesised systems map for critique and validation.
FINDINGS: Hand-created maps evolved into a validated CLD, containing 49 elements connected by 130 causal links and 5 feedback loops. These loops revealed how demand generation, supply chain capacity, economic viability, trust and product consistency, and infrastructural constraints, reinforce or balance system performance. Six themes emerged: (i) demand generation, (ii) supply chain constraints, (iii) economic viability, (iv) social innovation and trust, (v) nutritional guidance and (vi) unintended consequences. The CLD also enabled interventions to be pinpointed within a system to inform policy/practice actions for change.
CONCLUSIONS: We illustrate how systems thinking and expert elicitation approaches have successfully encouraged dynamic dialogue to support the identification of future policy and practice interventions. This demonstrates how social innovation projects can be championed and their powerful potential for catalysing (blue) food system transformation better realised.

Keywords: blue food system transformation; causal loop diagram; collaborative processes; expert elicitation; policy; social innovation; systems mapping; systems thinking

DOI: https://doi.org/10.1111/jhn.70234

Health Expect. 2026 Apr;29(2): e70616

The 'Public' in Public Involvement: A Call to Centre Frontline Staff Voices in Health Workforce Research.

Yingxi Zhao, Justin Aunger, Hilary Garrett, Paul Hewitson, Alun Davies, Manish Pareek, Sassy Molyneux.

Public involvement, or patient and public involvement and engagement (PPIE), is widely embedded in health and care research and is valued for its moral, ethical, and methodological contributions. However, its application in workforce research raises important questions about the voices that might be missing from the 'public' when research's primary object of inquiry is healthcare staff, organisations, and systems, rather than patients and service users. This viewpoint explores tensions arising from the extension of standardised public involvement requirements, which were originally developed for research where patients and service users are the primary target of focus, into workforce-focused studies. We argue that while patient and public perspectives remain crucial, the lived experience and voices of frontline staff are often under-recognised in existing involvement frameworks, including those used in NIHR domestic programmes, as they are not fully accommodated within either public involvement or stakeholder engagement activities. We therefore call for greater clarity, flexibility, and, where appropriate, expansion in how public involvement is conceptualised and operationalised in workforce research, to better centre the voices of frontline staff. Rather than offering definitive solutions, we invite debate and future research on how public involvement can be made more meaningful, proportionate, and fit-for-purpose in health and care workforce research. PATIENT OR PUBLIC CONTRIBUTION: This viewpoint article is written by researchers in the health and care workforce, PPIE, and community engagement, and a public contributor with interest and experience of involvement in health and care workforce research. We drew on our respective perspectives and experience to shape the framing and arguments presented in this viewpoint.

Keywords: community engagement; co‐production; health services research; public participation

DOI: https://doi.org/10.1111/hex.70616

Appl Health Econ Health Policy. 2026 Mar 25.

A Systematic Review of Microsimulation Models in Cardiometabolic Disease: Model Calibration and Validation.

Danwei Yang, Zhixin Cao, Jayoung Byun, Jong-Wook Ban, David D Kim.

BACKGROUND: Microsimulation models are increasingly used to project health trajectories of individuals with cardiometabolic diseases, including type 2 diabetes, obesity, cardiovascular disease, and chronic kidney disease. Despite the emergence of practice guidelines on model calibration and validation, it remains unclear whether practices in model development and reporting have improved accordingly.
OBJECTIVE: To summarize the characteristics of studies reporting cardiometabolic disease microsimulation models, assess how calibration and validation processes are reported, and examine variations in reporting practices by study characteristics.
METHODS: We searched PubMed, Embase, and Web of Science for studies reporting the original development of microsimulation models of cardiometabolic diseases published between 2016 and June 1, 2024. Studies reporting calibration and/or validation processes were included. We recorded study characteristics and assessed reporting adherence to six calibration processes (defining parameters, selecting targets, applying search strategies, specifying convergence criteria, establishing stopping rules, and selecting goodness-of-fit measures) and five validation processes (face validity, verification, cross-validation, external validation, and predictive validation) based on published practice guidelines. We further investigated variation in guideline adherence by study characteristics (modeling type, cardiometabolic diseases, publication year, baseline population data source, modeling country, simulation tool, and open-source status). This study is registered in PROSPERO (CRD42024562800).
RESULTS: Of 2646 studies screened, 31 were included in the final sample. Sixteen studies (52%) reported application-based model development and 15 (48%) reported natural history model development; 7 (23%) made their code publicly available; and 8 (26%) simulated three or more diseases. For calibration, 23 studies (74%) reported at least one of the six processes, most often specifying calibration targets (n = 22, 71%) and calibrated parameters (n = 21, 68%). For validation, 26 studies (84%) reported at least one of the five processes, most commonly external validation (n = 19, 61%), but no study reported predictive validation. Studies that developed natural history models more often reported goodness-of-fit measures, stopping rules, and external validation than application-based models. Studies that open-sourced their code reported statistical goodness-of-fit measures more frequently than those that did not. Models simulating three or more diseases more often documented face validity and verification than those simulating fewer diseases.
CONCLUSIONS: Reporting of calibration and validation in recent microsimulation models has improved, but important gaps remain. We suggest that future work prioritize (1) more rigorous calibration and validation in application-based model development, (2) clearer reporting of calibration processes, particularly parameter search strategies and convergence criteria, (3) stronger quantitative performance measures for external validation and greater use of predictive validation, and (4) broader adoption of open-source practices to enhance transparency and reproducibility.

DOI: https://doi.org/10.1007/s40258-026-01036-4

PRiMER. 2026 ;10 11

Application of Group Concept Mapping in Medical and Public Health Education.

Scott Rosas.

Introduction: Group concept mapping (GCM) is a mixed-method participatory research approach that integrates stakeholder input to visually represent complex ideas and issues. Within medical and public health education, GCM has gained traction for its ability to synthesize diverse perspectives and guide decision-making in curriculum development, assessment, and support strategies.
Methods: This article details the GCM methodology and synthesizes the literature on its applied use in medical and public health education. Included studies employed GCM's multistep process-idea generation, sorting and rating, data analysis, and stakeholder interpretation-to identify thematic structures and inform educational practices. Studies involved varied participant groups, including students, faculty, health care providers, and community stakeholders, using both online and in-person modalities.
Results: Across studies, GCM was used to address curriculum alignment, competency. development, student well-being, mentorship, diversity, and assessment. For instance, GCM revealed educational blind spots, guided development of interdisciplinary competencies, and prioritized public health outcomes. It also identified resilience factors and mentorship qualities critical for student and faculty development. In assessment contexts, GCM structured feedback mechanisms and clarified selection criteria for residency programs. The method consistently provided structured, stakeholder-informed visual maps to inform actionable changes.
Conclusions: GCM has proven to be a versatile and effective tool in medical and public health education. Its participatory nature enhances relevance, content validity, and stakeholder engagement, while its structured outputs support curricular reforms, competency development, and equity-driven initiatives. As the educational landscape evolves, GCM offers a valuable methodology for navigating complexity and fostering inclusive, evidence-informed strategies.

DOI: https://doi.org/10.22454/PRiMER.2026.559339