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Identifying high- and low-success smoking cessation subgroups using signal detection analysis. | LitMetric

Identifying high- and low-success smoking cessation subgroups using signal detection analysis.

Addict Behav

VA San Diego Healthcare Systems and UCSD, MC116A4Z, San Diego, CA 92130, USA.

Published: January 2006

Signal detection analysis was used to identify mutually exclusive groups of smokers (n = 602) at high and low likelihood for smoking cessation 6- and 18-months post-entry into a smoking cessation intervention. Overall quit rates were 10% at 6-months and 18% at 18-months. Four subgroups were identified at 6-months and five at 18-months. The highest quit-rate subgroup at both time points (42% and 52% cessation, respectively) had low perceived stress. The lowest quit-rate subgroup (7% and 13% cessation, respectively) had higher perceived stress, lower self-efficacy to not smoke, lower use of behavioral processes at 6-months, and higher use of pros of smoking at 18-months. These smoker profiles may be useful in developing targeted smoking cessation interventions. Addressing perceived stress in smoking cessation interventions may help to improve smoking cessation success rates.

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Source
http://dx.doi.org/10.1016/j.addbeh.2005.04.019DOI Listing

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