Katja Wiemer-Hastings, Adrian S Janit, Peter M Wiemer-Hastings, Steve Cromer, Jennifer Kinser
{"title":"Automatic classification of dysfunctional thoughts: a feasibility test.","authors":"Katja Wiemer-Hastings, Adrian S Janit, Peter M Wiemer-Hastings, Steve Cromer, Jennifer Kinser","doi":"10.3758/bf03195565","DOIUrl":null,"url":null,"abstract":"<p><p>The identification of dysfunctional thoughts is a central effort in cognitive therapy. This paper describes the first version of a computer module that classifies dysfunctional thoughts automatically. It is part of COGNO, a system we are developing to give automatic feedback on dysfunctional thoughts. The system uses rules that were developed from language markers identified in a sample of 149 dysfunctional thoughts. The system was tested with an independent set of 112 example thoughts. The system detects the majority of dysfunctional thoughts, but works reliably only for some thought categories. Automatic thought classification may be a first step toward developing natural dialogue systems in cognitive therapy.</p>","PeriodicalId":79800,"journal":{"name":"Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc","volume":"36 2","pages":"203-12"},"PeriodicalIF":0.0000,"publicationDate":"2004-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3758/bf03195565","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3758/bf03195565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The identification of dysfunctional thoughts is a central effort in cognitive therapy. This paper describes the first version of a computer module that classifies dysfunctional thoughts automatically. It is part of COGNO, a system we are developing to give automatic feedback on dysfunctional thoughts. The system uses rules that were developed from language markers identified in a sample of 149 dysfunctional thoughts. The system was tested with an independent set of 112 example thoughts. The system detects the majority of dysfunctional thoughts, but works reliably only for some thought categories. Automatic thought classification may be a first step toward developing natural dialogue systems in cognitive therapy.