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Determining socially relevant responses in patients with an ambiguous state of consciousness

Activity: Talk or presentation typesLecture and oral contribution

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Hanne Bess Boelsbjerg - Invited speaker

Mette Terp Høybye - Other

Lise Marie Andersen - Other

Supporting patients with unresponsive wakefulness syndrome (UWS) and minimally consciousness states (MCS) involves the use of multiple technologies, relying on medical treatments, monitoring and clinical practices. Assessments of the ambiguous state of consciousness in such patients by health care professionals (HCP) are informed by these technologies, often not realizing the social interaction and interpretation technologies involve.

Based on an extensive anthropological fieldwork in a highly specialized intensive care unit, we follow HCPs in their interaction with UWS and MCS patients.

Displayed as vital bodily functions of heart rate, temperature and oxygen saturation, continuously and closely monitored, the HCP is allowed to ‘read’ the patient through the monitors. Interpreted as signs, also to determine patients’ responses to social stimuli as e.g. family visits.

Clinical practices such as touch, movement, visual assessments and audible prompts supplement digital monitoring. These practices depend on patients’ ability to respond to stimuli that is socially conditioned by the clinical interaction with a specific HCP and the context. To sense and register the response and interpret it as relevant, which may indicate some level of consciousness, HCPs must be able to engage socially with the patient.

By exploring the interdependence of socially relevant responses to the clinical engagement of monitoring and sensory practices, we seek to discuss how consciousness is perceived and performed in relation to UWS and MCS patients. Hereby we seek to exemplify how the use of medical technologies in highly specialized clinical settings is embedded in and influenced by sensory engagement and relational practices.

7 Oct 202110 Oct 2021

External organisation (Academic)

NameUniversity of Vienna

ID: 229894517