Aim To examine whether Rasch modeling would yield a unidimensional withdrawal sensitivity measure correlating with factors associated with successful smoking cessation.
Design The psychometric Rasch modeling approach was applied to estimate an underlying latent construct (withdrawal sensitivity) in retrospective responses from 1644 smokers who reported quitting for 3 or more months at least once.
Setting Web-based, passcode-controlled self-administered computerized questionnaire.
Participants Randomly selected convenience sample of 1644 adult members of an e-mail invitation-only web panel drawn from consumer databases.
Measurements Lifetime Tobacco Use Questionnaire, assessing tobacco use across the life-span, including demographics and respondent ratings of the severity of withdrawal symptoms experienced in respondents' first and most recent quit attempts lasting 3 or more months.
Findings Rasch-modeled withdrawal sensitivity was generally unidimensional and was associated with longer periods of smoking cessation. One latent variable accounted for 74% of the variability in symptom scores. Rasch modeling with a single latent factor fitted withdrawal symptoms well, except for increased appetite, for which the fit was marginal. Demographic variables of education, gender and ethnicity were not related to changes in sensitivity. Correlates of greater withdrawal sensitivity in cessation attempts of at least 3 months included younger age at first quit attempt and indicators of tobacco dependence.
Conclusion The relationship between tobacco dependence symptoms and Rasch-model withdrawal sensitivity defines further the relationship between sensitivity and dependence. The findings demonstrate the utility of modeling to create an individual-specific sensitivity measure as a tool for exploring the relationships among sensitivity, dependence and cessation.