(2011) regard the interval at which smokers need to smoke as a core index of the progression of dependence. This is not a definitive test, as DiFranza Dorsomorphin IC50 et al. (2011) suggest people may sometimes smoke without needing to, but it does suggest the need for a more effective measure. In any case, the continuous HONC seems more sensitive to variations in dependence behaviors among ITS. As expected, the Primary Dependence scale of the WISDM was more strongly associated with dependence outcomes among ITS than was the Secondary motives scale of the WISDM. Indeed, the Primary Dependence scale of the WISDM consistently showed the numerically strongest relationships to the behavioral indicators of dependence we tested, perhaps, because its length confers greater reliability.

The FTND, TTFC, and NDSS measures performed roughly comparably with correlations consistently slightly less than those seen for WISDM Primary and higher than those seen for WISDM Secondary and HONC. Interestingly, for the variables relating to abstinence rather than smoking rate��the proportion of days smoking and the longest run of abstinence��TTFC on its own seem to do as well or better than the entire FTND (which incorporates TTFC), suggesting that the other elements of FTND actually diluted rather than enhanced the information imparted by TTFC. Like any study, our study suffered some limitations. This was a limited convenience sample from a single region, so may not be fully representative, particularly in its lack of subjects of Asian and Hispanic descent, who have higher rates of ITS (Trinidad et al.

, 2009). All the data were collected by self-report, albeit some using real-time EMA. However, reports of abstinence were not biochemically verified, and we examined periods of voluntary abstinence, rather than the outcomes of smoking cessation efforts. The study also had considerable strengths. We assessed several measures of dependence and several different dependence-relevant behavioral outcomes. Smoking behavior was assessed by EMA methods, which have been biochemically validated in other studies (Shiffman, 2009a), and demonstrated superior to time-line follow-back methods for assessing day-to-day smoking patterns. In summary, the study confirmed that DS have much stronger dependence than ITS and that CITS are more dependent than NITS.

At the AV-951 same time, the data showed that there is meaningful variation in dependence among ITS. The implications of this for ITS�� potential progression to daily smoking and for their success at quitting remains to be explored. Funding This work was supported by the National Institutes of Health , National Institute on Drug Abuse (R01-DA020742) to SS, the National Science Foundation Graduate Research Fellowship to MSD, the National Cancer Institute (R25-CA057703-15) to MSD, and Cancer Council Tasmania SGF.