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Linguistic Indicators of Severity and Progress in Online Text-based Therapy for Depression

Howes, C., Purver, M. and McCabe, R. ORCID: 0000-0003-2041-7383 (2014). Linguistic Indicators of Severity and Progress in Online Text-based Therapy for Depression. Paper presented at the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, 27 June 2014, Baltimore Maryland, USA.

Abstract

Mental illnesses such as depression andanxiety are highly prevalent, and therapyis increasingly being offered online. Thisnew setting is a departure from face-to-face therapy, and offers both a challengeand an opportunity – it is not yet knownwhat features or approaches are likely tolead to successful outcomes in such a dif-ferent medium, but online text-based ther-apy provides large amounts of data for lin-guistic analysis. We present an initial in-vestigation into the application of compu-tational linguistic techniques, such as topicand sentiment modelling, to online ther-apy for depression and anxiety. We findthat important measures such as symptomseverity can be predicted with compara-ble accuracy to face-to-face data, usinggeneral features such as discussion topicand sentiment; however, measures of pa-tient progress are captured only by finer-grained lexical features, suggesting thataspects of style or dialogue structure mayalso be important.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: Published in Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality Baltimore, Maryland, USA: ASsociation for Computational Linguistics. pp. 7-16. https://www.aclweb.org/anthology/W14-3202. doi: 10.3115/v1/W14-3202
Subjects: B Philosophy. Psychology. Religion > BF Psychology
P Language and Literature > P Philology. Linguistics
Departments: School of Health Sciences > Healthcare Services Research & Management
URI: http://openaccess.city.ac.uk/id/eprint/21762
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