Currently submitted to: JMIR Formative Research
Date Submitted: Nov 5, 2026
Open Peer Review Period: Nov 5, 2026 - Dec 31, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Developing a Contextual Framework for Cognitive Digital Twins in Surgery: An Exploratory Interdisciplinary Survey to Inform a Delphi Consensus Study
ABSTRACT
Background:
Cognitive digital twins (CDTs) represent a subset of digital twins, which are dynamic digital representations of real-world objects or processes, generated using data collected from sensors. CDTs using cognitive or neurophysiological data i.e. data reflecting human cognitive processes have huge potential within the surgical field, they could model how different intraoperative scenarios affect the mental workload of the surgeon or wider operating team. This could provide a platform for identifying and modifying factors contributing to excessive or insufficient cognitive demand, with the aim of maintaining workload within an optimal range.
Objective:
The aim of this study was to use the results of survey disseminated to a multidisciplinary audience to devise a framework to guide a future Delphi consensus study on the topic of CDTs in surgery.
Methods:
A survey was conceived highlighting key areas with an information-gap pertaining to CDTs. This was disseminated to participants of a multi-disciplinary workshop titled ‘Physics- and AI-Driven Digital Twins for Patient-Specific Robotic Diagnosis, Interventions and Therapies’. Demographic data was collected and open-ended questions were used in four domains. Qualitative data were analysed by content analysis by two independent reviewers, who then collated their results after review. A framework was created using the results.
Results:
There was a response rate of 13/27 (48%) participants, with an equal distribution of clinicians and researchers/academics. 12 coded domains were derived from content analysis and found to vary in frequency throughout the four survey sections. No single domain was represented as a majority amongst respondents. The analysis from the survey was used to create a robust framework centred around the translational pathway and key challenges from conception to clinical application.
Conclusions:
More work needs to be achieved on identifying key issues and solutions to hurdles within the translational pipeline and multidisciplinary collaboration are vital. The framework could be used to help a steering group guide formation of the Delphi first round/qualitative questions
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