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Improving self‐reports of drug‐use: numeric estimates as fuzzy sets
Author(s) -
Matt Georg E.,
Turingan Maria R.,
Dinh Quyen T.,
Felsch Julie A.,
Hovell Melbourne F.,
Gehrman Christine
Publication year - 2003
Publication title -
addiction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.424
H-Index - 193
eISSN - 1360-0443
pISSN - 0965-2140
DOI - 10.1046/j.1360-0443.2003.00444.x
Subject(s) - fuzzy logic , computer science , drug , medicine , psychology , artificial intelligence , pharmacology
Aims This study compared traditional crisp set to fuzzy set representations of quantitative estimates of drug use to investigate what survey respondents recall about their drug use. Design Sample survey comparing (a) responses to traditional survey questions asking for single numeric estimates to (b) responses to fuzzy set questions asking for boundary estimates of drug use. Setting Research facilities of a public university in a large southern California city. Participants Community residents using tobacco, alcohol, marijuana or amphetamine ( n = 88). Measurements Personal interviews in which participants reported onset, frequency and daily rate of tobacco, alcohol, marijuana and amphetamine use based on traditional survey questions and fuzzy set questions. Findings With the exception of marijuana use, fuzzy boundary estimates differed significantly from the traditional point estimates ( P < 0.05). Median retest reliabilities for fuzzy boundary estimates were 0.96 (tobacco), 0.81 (alcohol), 0.96 (marijuana) and 0.95 (amphetamine). The degree of vagueness varied by behavior and drug, with estimates of daily rates showing greatest fuzziness and onset of use showing least fuzziness. Conclusions Participants recall more about past drug use than a single numeric estimate. All numeric estimates of drug use showed fuzzy set properties. Compared to traditional self‐reports of drug use, fuzzy set representations provide a more complete and detailed description of what participants recall about past drug use.