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Artificial intelligence in critical synthesis of public health responses to violence: A novel application to UK violence prevention policy.

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Τίτλος: Artificial intelligence in critical synthesis of public health responses to violence: A novel application to UK violence prevention policy.
Συγγραφείς: Cook D; Violence and Society Centre, City St George's, University of London, London, UK. Electronic address: Darren.Cook@citystgeorges.ac.uk., Cook E; Violence and Society Centre, City St George's, University of London, London, UK., Cullen K; Violence and Society Centre, City St George's, University of London, London, UK., Zachos K; Institute for Creativity and AI, City St George's, University of London, London, UK., McManus S; Violence and Society Centre, City St George's, University of London, London, UK., Bellis MA; Public Health Institute, WHO Collaborating Centre for Violence Prevention, Liverpool John Moores University, Liverpool, UK., Feder GS; Centre for Academic Primary Care, University of Bristol, Bristol, UK., Maiden N; Institute for Creativity and AI, City St George's, University of London, London, UK.
Πηγή: Public health [Public Health] 2026 Jun; Vol. 255, pp. 106258. Date of Electronic Publication: 2026 Apr 13.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0376507 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-5616 (Electronic) Linking ISSN: 00333506 NLM ISO Abbreviation: Public Health Subsets: MEDLINE
Imprint Name(s): Publication: 2003- : Amsterdam : Elsevier
Original Publication: London ; New York : Academic Press
Ιατρικοί όροι (MeSH): Violence*/prevention & control , Artificial Intelligence* , Public Health* , Health Policy*, United Kingdom ; Humans ; Policy Making ; Public Policy ; Proof of Concept Study
Περίληψη: Objectives: Artificial intelligence (AI) systems are increasingly applied in public health, yet their use for analysing fragmented, multi-sectoral policy landscapes remains underdeveloped. This study aimed to describe the development and preliminary exploration of an AI-enabled tool designed to synthesise evidence from violence-related policy documents in the UK.
Study Design: An exploratory, proof-of-concept case study.
Methods: A corpus of publicly available UK policy and strategy documents on violence (N = 343) was compiled through expert review, manual searches of government and third sector organisation websites, and automated web scraping. We used the corpus to train an existing AI framework and deployed it through a question-answer interface. Stakeholders were invited to pose natural-language questions about violence policy and consider the system's utility and the usefulness of its outputs.
Results: Stakeholders reported that the AI-enabled tool facilitated flexible interrogation of violence-related policy documents and supported identification of recurring framings, sectoral differences, and potential policy siloes. Feedback indicated that the system improved the efficiency and transparency of cross-sectoral policy analysis, particularly in the initial stages of an inquiry.
Conclusions: This short communication provides early insight into the potential of AI-enabled tools to support public health policy analysis by structuring and synthesising complex documentary evidence. Such functionality is particularly relevant in areas requiring cross-sectoral collaboration. Further work is required to formally evaluate performance, assess bias, and explore impacts of AI on real-world decision-making prior to wider implementation.
(Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Competing Interests: Declaration of competing interest The authors have no conflicts of interest.
Contributed Indexing: Keywords: Artificial intelligence; Evidence synthesis; Large language models; Policy analysis; Public health policy; Violence and abuse
Entry Date(s): Date Created: 20260414 Date Completed: 20260714 Latest Revision: 20260714
Update Code: 20260715
DOI: 10.1016/j.puhe.2026.106258
PMID: 41980577
Βάση Δεδομένων: MEDLINE
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  Data: Artificial intelligence in critical synthesis of public health responses to violence: A novel application to UK violence prevention policy.
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  Data: <searchLink fieldCode="AU" term="%22Cook+D%22">Cook D</searchLink>; Violence and Society Centre, City St George's, University of London, London, UK. Electronic address: Darren.Cook@citystgeorges.ac.uk.<br /><searchLink fieldCode="AU" term="%22Cook+E%22">Cook E</searchLink>; Violence and Society Centre, City St George's, University of London, London, UK.<br /><searchLink fieldCode="AU" term="%22Cullen+K%22">Cullen K</searchLink>; Violence and Society Centre, City St George's, University of London, London, UK.<br /><searchLink fieldCode="AU" term="%22Zachos+K%22">Zachos K</searchLink>; Institute for Creativity and AI, City St George's, University of London, London, UK.<br /><searchLink fieldCode="AU" term="%22McManus+S%22">McManus S</searchLink>; Violence and Society Centre, City St George's, University of London, London, UK.<br /><searchLink fieldCode="AU" term="%22Bellis+MA%22">Bellis MA</searchLink>; Public Health Institute, WHO Collaborating Centre for Violence Prevention, Liverpool John Moores University, Liverpool, UK.<br /><searchLink fieldCode="AU" term="%22Feder+GS%22">Feder GS</searchLink>; Centre for Academic Primary Care, University of Bristol, Bristol, UK.<br /><searchLink fieldCode="AU" term="%22Maiden+N%22">Maiden N</searchLink>; Institute for Creativity and AI, City St George's, University of London, London, UK.
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  Label: Abstract
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  Data: Objectives: Artificial intelligence (AI) systems are increasingly applied in public health, yet their use for analysing fragmented, multi-sectoral policy landscapes remains underdeveloped. This study aimed to describe the development and preliminary exploration of an AI-enabled tool designed to synthesise evidence from violence-related policy documents in the UK.<br />Study Design: An exploratory, proof-of-concept case study.<br />Methods: A corpus of publicly available UK policy and strategy documents on violence (N = 343) was compiled through expert review, manual searches of government and third sector organisation websites, and automated web scraping. We used the corpus to train an existing AI framework and deployed it through a question-answer interface. Stakeholders were invited to pose natural-language questions about violence policy and consider the system's utility and the usefulness of its outputs.<br />Results: Stakeholders reported that the AI-enabled tool facilitated flexible interrogation of violence-related policy documents and supported identification of recurring framings, sectoral differences, and potential policy siloes. Feedback indicated that the system improved the efficiency and transparency of cross-sectoral policy analysis, particularly in the initial stages of an inquiry.<br />Conclusions: This short communication provides early insight into the potential of AI-enabled tools to support public health policy analysis by structuring and synthesising complex documentary evidence. Such functionality is particularly relevant in areas requiring cross-sectoral collaboration. Further work is required to formally evaluate performance, assess bias, and explore impacts of AI on real-world decision-making prior to wider implementation.<br /> (Copyright © 2026 The Authors. Published by Elsevier Ltd.. All rights reserved.)
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  Data: Declaration of competing interest The authors have no conflicts of interest.
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