Development and validation of a cluster-based classification system to facilitate treatment tailoring

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Abstract

AIMS

The objectives of this study were to replicate smoker profiles identified in Batra et al. (in press) and to develop a cluster-based classification system to categorize new cases into smoker profiles so that an appropriate tailored intervention could be applied.

Methods

Participants were smokers in south west Germany who sought treatment for smoking cessation. In the first sample, discriminant analysis was used to create classification formulas for a future study (classification sample: n = 165). The second sample served to replicate the smoker profiles, which included participants reporting symptoms of hyperactivity/novelty-seeking, depressivity or high nicotine dependence as well as participants scoring low across smoking and psychological variables (replication sample: N = 13 4).

Results

Part 1 was focused on the development of formulas, using Fisher's coefficients, with which new cases could be classified. Part 2 adequately replicated previous findings concerning the smoker profiles, such that 70% of participants in the second sample were classified identically using cluster analysis and classification formulas.

Conclusions

The smoker profiles found in a previous study were replicated, and a classification system was developed for a future study which will test the efficacy of tailored treatments for the different smoker profiles.

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