Title
Identifying high- and low-success smoking cessation subgroups using signal detection analysis
Document Type
Article
Date of Original Version
1-1-2006
Abstract
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. © 2005 Elsevier Ltd. All rights reserved.
Publication Title, e.g., Journal
Addictive Behaviors
Volume
31
Issue
1
Citation/Publisher Attribution
Norman, Sonya B., Gregory J. Norman, Joseph S. Rossi, and James O. Prochaska. "Identifying high- and low-success smoking cessation subgroups using signal detection analysis." Addictive Behaviors 31, 1 (2006): 31-41. doi: 10.1016/j.addbeh.2005.04.019.