Lessons from a failure: Generating tailored smoking cessation letters.

Ehud Baruch Reiter, Roma Robertson, Liesl Marten Osman

Research output: Contribution to journalArticle

117 Citations (Scopus)

Abstract

STOP is a Natural Language Generation (NLG) system that generates short tailored smoking cessation letters, based on responses to a four-page smoking questionnaire. A clinical trial with 2553 smokers showed that STOP was not effective; that is, recipients of a non-tailored letter were as likely to stop smoking as recipients of a tailored letter. In this paper we describe the STOP system and clinical trial. Although it is rare for AI papers to present negative results, we believe that useful lessons can be learned from STOP. We also believe that the At community as a whole could benefit from considering the issue of how, when, and why negative results should be reported; certainly a major difference between AI and more established fields such as medicine is that very few AI papers report negative results. (C) 2002 Elsevier Science B.V All rights reserved.

Original languageEnglish
Pages (from-to)41-58
Number of pages17
JournalArtificial Intelligence
Volume144
Issue number(1-2)
DOIs
Publication statusPublished - Mar 2003

Keywords

  • natural language processing
  • natural language generation
  • knowledge acquisition
  • user modelling
  • AI and medicine
  • smoking cessation
  • evaluation
  • AI methodology
  • clinical trials
  • negative results
  • RANDOMIZED CONTROLLED TRIAL
  • CHANGE MODEL
  • INFORMATION
  • PUBLICATION
  • PREVENTION
  • SCHOOLS

Cite this

Lessons from a failure: Generating tailored smoking cessation letters. / Reiter, Ehud Baruch; Robertson, Roma; Osman, Liesl Marten.

In: Artificial Intelligence, Vol. 144, No. (1-2), 03.2003, p. 41-58.

Research output: Contribution to journalArticle

Reiter, Ehud Baruch ; Robertson, Roma ; Osman, Liesl Marten. / Lessons from a failure: Generating tailored smoking cessation letters. In: Artificial Intelligence. 2003 ; Vol. 144, No. (1-2). pp. 41-58.
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