The Axe Santé is organising a Health Tech Lunch on Thursday, June 2nd from 12:00 to 12:45 at Swiss Digital Center in Sierre (room Maïa).
Jakub Mlynar (Human-Centered Computing Group, IIG, HES-SO, Sierre) is a sociologist working at the University of Applied Sciences Western Switzerland (HES-SO Valais/Wallis). His recent research focuses on the use of digital technology in educational settings. In all his work, Jakub has been primarily interested in the communicative and interactional foundation of social order, exhibited by members of society through verbal and non-verbal means.
https://www.researchgate.net/profile/Jakub-Mlynar
Video-based studies of social interaction in healthcare settings
My talk will introduce video ethnography and multimodal conversation analysis as approaches to the study of social interaction in healthcare settings. The specificity of this research orientation rests in data-driven inductive analysis, starting from noticing phenomena of interest, building collections of similar occurrences, leading to systematic comparative analysis, towards precise description and explication of the practical conduct. These methods allow researchers to capture details of social activities, including medical settings, that are “acknowledged but tacit and unexamined” by participants as part of their work (Garfinkel 2022: 21). Such real-time features are analytically observable but often unavailable to classic post-hoc inquiries such as qualitative interviews or survey questionnaires.
Video-based interactionist studies of healthcare and hospital settings constitute a long-established field (Barnes 2019), including oncology (Singh et al. 2017) and radiology (Rystedt et al. 2011). As a case in point, and to illustrate some principles of this approach, I will look at a corpus of recordings of video-mediated interaction (see Mlynar et al. 2018) collected as part of the ExPlanatory radiomICS (EPICS) project (https://bit.ly/3pwgjHV). The project was situated in the novel field of medical imaging analysis known as radiomics – extracting large-scale quantitative features from medical imaging by AI algorithms (see Guiot et al. 2021 for a review). One of the main outcomes of the EPICS project was the online platform QuantImage, which allows extracting several types of features from Positron Emission Tomography/Computed Tomography (PET/CT) images, providing a simple and user-friendly environment that can be further adjusted for more refined analyses (Dicente Cid et al. 2017). Discussing results of a preliminary study of online video recorded user trial sessions with QuantImage, I will demonstrate how students working with this platform make relevant their prior ordinary work practices, but also establish new routines in the use of the plaftorm over the course of the experiment.
References
Barnes, R. K. 2019. Conversation analysis of communication in medical care: Description and beyond. Research on Language and Social Interaction 52(3): 300–315.
Dicente Cid, Y., et al. 2017. QuantImage: An online tool for high-throughput 3D radiomics feature extraction in PET-CT. In Biomedical texture analysis: Fundamentals, tools and challenges (pp. 365–394). London: Academic Press.
Garfinkel, H. 2022. Harold Garfinkel: Studies of Work in the Sciences. New York: Routledge.
Guiot, J. et al. 2021. A review in radiomics: Making personalized medicine a reality via routine imaging. Medicinal Research Reviews [early view].
Mlynar, J. et al. 2018. Situated organization of video-mediated interaction: A review of ethnomethodological and conversation analytic studies. Interacting with Computers 30(2): 73–84.
Rystedt, H. et al. 2011. Rediscovering radiology: New technologies and remedial action at the worksite. Social Studies of Science 41(6): 867–891.
Singh, S. et al. 2017. Characterizing the Nature of Scan Results Discussions: Insights Into Why Patients Misunderstand Their Prognosis. Journal of Oncology Practice 13(3): 231–239.
Programme:
Registration : https://doodle.com/meeting/organize/id/dR6KqNKd