Examining linguistic cues for predicting mental health status

• Main Author: Long, Xiang Ni
• Other Authors: Goh Wen Bin Wilson
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Social sciences::Psychology
• Online Access: https://hdl.handle.net/10356/152332
• Institution: Nanyang Technological University

Individuals with schizophrenia contribute substantially to the global burden of disease, despite having a low prevalence rate. It is a chronic mental health disorder that leads to a decrease in quality of life if prompt treatment is not given. Differences in language features of ultra-high risk (UHR) individuals (n=360) were compared with healthy controls (n=86). UHR individuals shows a significant increase in production of pauses and a relative increase in type-token ratio, but a decrease in total number of words spoken when compared to healthy controls (all with p value<0.05). Results reveal that linguistic cues may provide another avenue when trying to determine the mental state of individuals at high risk of developing psychosis.