A randomised cross over trial examining the linguistic markers of depression and anxiety in symptomatic adults.

Abstract

Linguistic features within individuals' text data may indicate their mental health. This trial examined the linguistic markers of depressive and anxiety symptoms in adults. Using a randomised cross over trial design, 218 adults provided eight different types of text data of varying frequencies and emotional valance. Linguistic features were extracted using LIWC-22 and correlated with self-reported symptoms. Machine learning was used to determine associations. No linguistic features were consistently associated with depressive or anxiety symptoms within or across all tasks. Features associated with depressive symptoms were different for each task and there was only some degree of reliability of these features within tasks. In all machine learning models, predicted values were weakly associated with actual values. Some text tasks had lower levels of engagement and negative impacts on mood. Overall, the linguistic markers of depression and anxiety shifted in response to contextual factors and the nature of the text analysed. This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (date registered: 15 September 2021, ACTRN12621001248853).