Voice-based Digital Health Interventions (DHIs), such as the GRACE voice assistant being developed at the Centre for Digital Health Interventions (CDHI) [1, 2], offer a promising way to support the well-being of individuals with dementia. However, to develop and test these tools safely and effectively, we need to ground them in a deep understanding of the communication patterns of this population [3, 4]. The critical first step is to systematically map the existing scientific evidence on how dementia alters speech and language.

Scope of the thesis

This thesis will involve conducting a structured and comprehensive scoping review of the scientific literature to identify and categorize the linguistic biomarkers associated with early-stage dementia. The primary goal is to synthesize the current state of research from fields like neurology, psycholinguistics, and computational linguistics. The final output will be a comprehensive review article that maps the existing evidence, identifies key research trends, and highlights gaps in our current understanding. This work will serve as a foundational resource for future projects, including the development of clinically-informed AI personas for the GRACE project.

Major tasks include, but are not limited to

• Develop a clear research question and a review protocol
• Conduct a systematic search of relevant academic databases
• Screen articles for eligibility based on predefined criteria
• Extract and chart relevant data from the included studies
• Synthesize and analyze the findings to provide a comprehensive overview of the topic

We offer

Embarking on a thesis journey with us should be a mutually rewarding and engaging experience. We always work in interdisciplinary teams, and you’ll be closely supervised. You will be part of the Centre for Digital Health Interventions (CDHI), a joint initiative of ETH Zurich, the University of St.Gallen, and the University of Zurich. Results of the thesis will be published in a peer-reviewed scientific journal.

Who Should Apply?

We seek a self-driven and intrinsically motivated student with a background in health sciences, (computational) linguistics, psychology, computer science, or a related field. Experience with systematic literature reviews is a plus. Strong analytical skills, attention to detail, and a passion for exploring the intersection of medicine and technology are essential. Interested students are invited to submit a brief statement of interest and their CV to Felix Moser (felix.moser@unisg.ch).