Belinda Borrelli1, Rashelle B Hayes, Shira Dunsiger, Joseph L Fava. 1. Centers for Behavioral and Preventive Medicine, Warren Alpert Medical School of Brown University and The Miriam Hospital, Providence, RI 02903, USA. belinda_borrelli@brown.edu
Abstract
AIMS: To examine the influence of risk perception on intentions to quit smoking and post-treatment abstinence. DESIGN: Prospective and longitudinal. SETTING: United States. PARTICIPANTS: A total of 237 adult smokers (mean age 56 years) receiving medical care from home health-care nurses. Participants did not have to want to quit smoking to participate, but received cessation counseling within the context of their medical care. MEASUREMENTS: Three measures of risk perception were given pre- and post-treatment: perceived vulnerability, optimistic bias and precaution effectiveness. Smoking status was verified biochemically at end of treatment and at 2, 6 and 12 months later. FINDINGS: Principal components analysis supported the theoretical discriminability of the risk perception measures, and intercorrelations provided evidence for concurrent and predictive validity. Elevated risk perception was associated with a variety of socio-demographic and psychosocial characteristics. Optimistic bias was associated significantly with older age and ethnic minority status. Smokers in pre-contemplation had lower perceived vulnerability and precaution effectiveness and greater optimistic bias than those in contemplation and preparation. Smokers in preparation had higher perceived vulnerability and lower optimistic bias than those in earlier stages. Change in perceived vulnerability predicted smoking cessation at follow-up. Optimistic bias predicted a lower likelihood of cessation and precaution effectiveness predicted a greater likelihood of smoking cessation, but only among those with a smoking-related illness. CONCLUSIONS: In patients receiving medical care from home health-care nurses, change in perceived vulnerability to smoking-related disease is predictive of smoking cessation. In those with smoking-related illnesses, optimistic bias predicts continued smoking while precaution effectiveness predicts cessation.
RCT Entities:
AIMS: To examine the influence of risk perception on intentions to quit smoking and post-treatment abstinence. DESIGN: Prospective and longitudinal. SETTING: United States. PARTICIPANTS: A total of 237 adult smokers (mean age 56 years) receiving medical care from home health-care nurses. Participants did not have to want to quit smoking to participate, but received cessation counseling within the context of their medical care. MEASUREMENTS: Three measures of risk perception were given pre- and post-treatment: perceived vulnerability, optimistic bias and precaution effectiveness. Smoking status was verified biochemically at end of treatment and at 2, 6 and 12 months later. FINDINGS: Principal components analysis supported the theoretical discriminability of the risk perception measures, and intercorrelations provided evidence for concurrent and predictive validity. Elevated risk perception was associated with a variety of socio-demographic and psychosocial characteristics. Optimistic bias was associated significantly with older age and ethnic minority status. Smokers in pre-contemplation had lower perceived vulnerability and precaution effectiveness and greater optimistic bias than those in contemplation and preparation. Smokers in preparation had higher perceived vulnerability and lower optimistic bias than those in earlier stages. Change in perceived vulnerability predicted smoking cessation at follow-up. Optimistic bias predicted a lower likelihood of cessation and precaution effectiveness predicted a greater likelihood of smoking cessation, but only among those with a smoking-related illness. CONCLUSIONS: In patients receiving medical care from home health-care nurses, change in perceived vulnerability to smoking-related disease is predictive of smoking cessation. In those with smoking-related illnesses, optimistic bias predicts continued smoking while precaution effectiveness predicts cessation.
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