Lessons from a failure: Generating tailored smoking cessation letters
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...
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Veröffentlicht in: | Artificial intelligence 2003-03, Vol.144 (1), p.41-58 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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
ai 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. |
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ISSN: | 0004-3702 1872-7921 |
DOI: | 10.1016/S0004-3702(02)00370-3 |