Identifying high- and low-success smoking cessation subgroups using signal detection analysis
Article Abstract:
Signal detection methodology was applied to a sample of participants in a self-help smoking cessation study to create an algorithm with differentiated high- and low-rate quit groups. It was seen that identifying meaningful subgroups of smokers was one method by which to learn more about the mechanisms of quitting and how one could improve one's interventions.
Publication Name: Addictive Behaviors
Subject: Sociology and social work
ISSN: 0306-4603
Year: 2006
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Prevention profiles: understanding youth who do not use substances
Article Abstract:
Usage of transtheoretical model to analyze patterns and risk of substance use by adolescents and youth is described. The observations can be useful in preventing substance abuse.
Publication Name: Addictive Behaviors
Subject: Sociology and social work
ISSN: 0306-4603
Year: 2006
User Contributions:
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- Abstracts: Size, consistenc, and stability of stage effects for smoking cessation. A comparison of four self-report smoking cessation outcome measures
- Abstracts: Social and cognitive factors contributing to the intention to undergo a smoking cessation treatment. Identifying high-and low-success smoking cessation subgroups using signal detection analysis