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Executive Summary

Australians living in rural and remote areas face a unique combination of stressors, placing them at elevated risk of mental health problems. They also have poorer access to mental health services than those living in Australian cities. Compounding the problem of fewer available services are barriers to help-seeking, such as stigma and entrenched stoicism.

E-mental health services permit spanning great distances and have the potential to circumvent the barriers faced by clients in rural and remote communities using technology. Text-based services are particularly well suited to addressing the needs of Australians in rural and remote communities because they offer a level of anonymity not possible in traditional face-to-face, video-, or audio-based delivery methods, making them appealing to clients concerned with stigma, self- presentation and privacy. Moreover, they allow the client to reflect on the therapy session after it has ended as the transcript is stored on their phone (or another device). The text transcript also offers researchers an opportunity to analyse language use patterns and explore how these relate to mental health status.

In this project, we investigated whether computational linguistic techniques can be applied to text-based communications with the goal of identifying a client’s mental health status. The results confirmed that word use patterns could be used to differentiate whether a client had one of the top three presenting problems (depression, anxiety, or stress), as well as prospectively to predict their self-rated mental health after counselling had concluded. These findings suggest that language use patterns are useful both for researchers and for clinicians trying to identify individuals at risk of mental health problems, with potential applications in screening and targeted intervention.