This study aims to develop an ethical approach to developing and deploying novel neurotechnologies to aid in the detection of consciousness and prediction of recovery after brain injury.
Previous studies of patients with disorders of consciousness (DoC) have suggested that conscious patients may be misdiagnosed as unconscious up to 40% of the time when traditional qualitative bedside examination is used (Schnakers et al. 2009, Van Erp et al. 2015, Fins and Bernat 2018). Given the well-established prognostic relevance of early behavioral recovery of consciousness for long-term functional outcomes (Giacino and Kalmar 1997, Giacino 2004, Portaccio et al. 2018, Faugeras et al. 2018, Pincherle et al. 2019), whether or not a patient is considered to be conscious is often the primary determinant of whether life-sustaining therapy is continued and neurorehabilitation is offered. Recent advances in neuroimaging and electrophysiologic neurotechnologies, including functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), have yielded novel methods to aid in detecting and predicting emergence of consciousness in patients with brain injuries. Despite these unprecedented research advances, little is known about ethical concerns surrounding these novel neurotechnologies, about the phenomenological, ontological and ethical valence of conscious states of being without behaving revealed through their lens, or about the attitudes of clinicians, researchers, patients and caregivers regarding their responsible implementation. This study aims to fill these crucial knowledge gaps and to support the development of an evidence-based strategy for ensuring responsible research and translation of novel neurotechnologies to aid in the detection of consciousness and prediction of recovery after brain injury.
Study Type
OBSERVATIONAL
Enrollment
70
Surveys will serve to identify preferences, expectations and concerns among clinicians and researchers surrounding data-sharing of uncertain diagnostic data generated through investigative neurotechnologies which will then be systematically evaluated.
Semi-structured interviews will further serve to identify preferences, expectations and concerns among patients, surrogates, clinicians and researchers surrounding data-sharing of uncertain diagnostic data generated through these investigative neurotechnologies which will then be systematically evaluated.
Massachusetts General Hospital
Boston, Massachusetts, United States
RECRUITINGSurveys and semi-structured interviews
Capture and evaluate salient perspectives, preferences and values surrounding the use of advanced neurotechnologies to detect consciousness and predict recovery
Time frame: through study completion, an average of 1 year
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