Grant: DRA: Canada Impact+ Research Training Awards - Doctoral

"Artificial intelligence (AI) is increasingly used in mental health care through online chatbots, symptom checkers, and clinical decision support tools. For some people, these tools may offer quicker or more convenient access to help. For others, they raise concerns about privacy, bias, safety, and errors, especially when sensitive personal information is involved. How AI is accepted in mental health care depends in part on how it is publicly discussed and understood. This project will examine how trust, mistrust, and uncertainty about AI-enabled mental health tools are expressed and shared in public online conversations. We will analyze publicly available social media posts to identify the main issues raised and assess whether posts signal trust, mistrust, or uncertainty. The study will also examine how these narratives vary across online communities and shift over time, including around major news events (e.g., current concerns about safety of chatbots and suicide in youth). To complement this analysis of public discourse, the project will use data from Statistics Canada’s Canadian Internet Use Survey to examine predictors of trust in AI among people who report lower mental health. This analysis will assess how factors such as digital literacy, sociodemographic characteristics, and online experiences are associated with levels of trust in AI technologies. By combining large-scale online discourse analysis with nationally representative survey data, this research will clarify how AI mental health tools are framed publicly and which groups may be more or less likely to trust them. Findings will inform practical guidance for public health communication, technology developers, and health systems, supporting responsible and equitable use of AI in mental health care."