ArticleHealth services insights2026
Operationalising Inclusion for Participatory Design: Worked Examples for TRIPOD+AI & PROBAST+AI.
Article in Health services insights, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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.
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0 citing papers in PubMed.
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming the healthcare landscape, enhancing diagnostic accuracy, personalising treatments, and improving operational efficiency. However, alongside these advancements comes a critical concern: the potential for AI models to perpetuate, or even exacerbate, health inequities. This paper examines the complex potential of AI in health, and how it can both improve and undermine equity. The key to addressing these challenges lies not only in developing advanced algorithms but in fostering responsible and inclusive development. We argue that to operationalise inclusion in AI systems, research co-design should be prioritised in order to integrate the perspectives of diverse knowledge users, including patients, clinicians, and community partners, shown through worked examples in TRIPOD+AI and PROBAST+AI. This approach encourages future work to rethink the role of knowledge users in the development of AI for healthcare.
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Registered trials
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.