Research Supervisor Connect
Mental health stigma remains a major barrier to well-being, treatment-seeking, and social inclusion. Traditional biomedical models and public campaigns often frame mental illness as a “disease like any other,” assuming discrete boundaries between the mentally ill and the mentally healthy. While these approaches aim to reduce blame, research—including our own—shows they often exacerbate stigma by reinforcing perceptions of difference, increasing social distancing, and fostering pessimism about recovery. This project introduces an innovative alternative: targeting the discreteness bias—the belief that mental illness categories are rigid and non-overlapping.
Building on preliminary evidence that continuum-based narratives reduce stigma and increase perceived similarity between groups, this PhD project will systematically test whether undermining discreteness beliefs can reduce prejudice and improve outcomes for individuals with mental illness. Through a series of pre-registered experiments, the candidate will examine interpersonal effects (e.g., stigma reduction) and intrapersonal effects (e.g., willingness to disclose mental health struggles) among the general public and clinical populations. The research will also explore cross-cultural variations and mechanisms underlying these effects, such as perceived similarity and social dominance orientation.
This project offers a unique opportunity to contribute to cutting-edge stigma-reduction strategies with strong theoretical foundations and real-world implications. The successful candidate will gain expertise in experimental design, advanced statistical modeling, and intervention development, while collaborating with leading scholars in social and clinical psychology. The findings will inform public health campaigns and mental health advocacy, with the potential to transform how society understands and addresses mental illness.
This opportunity/project is part of the Faculty of Science Australian Research Council (ARC) Scholarship scheme and is now advertised on the Scholarship Office website. Applications are open and will close on 18 January 2026.
The opportunity ID for this research opportunity is 3725