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Using Treatment Process Data to Predict Maintained Smoking Abstinence
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Using Treatment Process Data to Predict Maintained Smoking Abstinence AMERICAN JOURNAL OF HEALTH BEHAVIOR Bailey, S. R., Hammer, S. A., Bryson, S. W., Schatzberg, A. F., Killen, J. D. 2010; 34 (6): 801-810Abstract
To identify distinct subgroups of treatment responders and nonresponders to aid in the development of tailored smoking-cessation interventions for long-term maintenance using signal detection analysis (SDA).The secondary analyses (n = 301) are based on data obtained in our randomized clinical trial designed to assess the efficacy of extended cognitive behavior therapy for cigarette smoking cessation. Model 1 included only pretreatment factors, demographic characteristics, and treatment assignment. Model 2 included all Model 1 variables, as well as clinical data measured during treatment.SDA was successfully able to identify smokers with varying probabilities of maintaining abstinence from end-of-treatment to 52-week follow-up; however, the inclusion of clinical data obtained over the course of treatment in Model 2 yielded very different partitioning parameters.The findings from this study may enable ÌÇÐÄ´«Ã½ers to target underlying factors that may interact to promote maintenance of long-term smoking behavior change.
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