Lounsbury, O., Pickup, L., Patriarca, Riccardo et al. (3 more authors) (2026) The functional resonance analysis method in healthcare: How knowledge is produced within and across scientific communities. Safety science. 107106. ISSN: 0925-7535
Abstract
The Functional Resonance Analysis Method (FRAM) is a valuable tool for understanding and improving complex socio-technical healthcare systems. This Focused Mapping Review and Synthesis (FMRS) explores how the FRAM is used to produce knowledge and create insight about healthcare systems across three scientific communities: safety/engineering, human factors/cognitive science, and healthcare/health services research. We examined 33 included studies and identified key themes in how FRAM is applied within and across communities. The review highlights the critical role of knowledge brokers and boundary spanners in fostering interdisciplinary collaboration and knowledge transfer. There is limited epistemological clarity in most studies, which complicates cross-study comparisons and practical application. In addition, most studies are descriptive and do not develop actionable and robust interventions. We argue for greater transparency in epistemological positioning, methodological reflexivity, and the development of reporting guidelines to enhance the consistency and utility of FRAM studies. This review is a conceptual synthesis rather than a proof of concept. Future empirical studies should test whether explicit articulation of epistemological assumptions improves FRAM analyses, using the probes identified in this review as a starting point.
Metadata
| Item Type: | Article |
|---|---|
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Authors. Published by Elsevier Ltd. |
| Keywords: | Epistemology,FRAM,Patient safety,Reporting guidelines,Resilience engineering |
| Dates: |
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| Institution: | The University of York |
| Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
| Date Deposited: | 11 Mar 2026 00:06 |
| Last Modified: | 30 Jun 2026 23:13 |
| Published Version: | https://doi.org/10.1016/j.ssci.2025.107106 |
| Status: | Published |
| Refereed: | Yes |
| Identification Number: | 10.1016/j.ssci.2025.107106 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:238942 |
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