Predicting treatment outcome from patient texts: The case of internet-based cognitive behavioural therapyVisa övriga samt affilieringar
2021 (Engelska)Ingår i: EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, Association for Computational Linguistics (ACL) , 2021, s. 575-580Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]
We investigate the feasibility of applying standard text categorisation methods to patient text in order to predict treatment outcome in Internet-based cognitive behavioural therapy. The data set is unique in its detail and size for regular care for depression, social anxiety, and panic disorder. Our results indicate that there is a signal in the depression data, albeit a weak one. We also perform terminological and sentiment analysis, which confirm those results.
Ort, förlag, år, upplaga, sidor
Association for Computational Linguistics (ACL) , 2021. s. 575-580
Nyckelord [en]
Computational linguistics, Sentiment analysis, Data set, Internet based, Social anxieties, Treatment outcomes, Patient treatment
Nationell ämneskategori
Tillämpad psykologi
Identifikatorer
URN: urn:nbn:se:ri:diva-53529Scopus ID: 2-s2.0-85107290691ISBN: 9781954085022 (digital)OAI: oai:DiVA.org:ri-53529DiVA, id: diva2:1568228
Konferens
16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021, 19 April 2021 through 23 April 2021
2021-06-172021-06-172024-05-15Bibliografiskt granskad