History and Correlates of Smoking Cessation Behaviors among Smokers with Serious Mental Illness

Abstract [from journal]

Introduction: Individuals with serious mental illness (SMI) smoke at rates 2-3 times greater than the general population but are less likely to receive treatment. Increasing our understanding of correlates of smoking cessation behaviors in this group can guide intervention development.

Methods: Baseline data from an ongoing trial involving smokers with SMI (N=482) were used to describe smoking cessation behaviors (i.e., quit attempts, quit motivation and smoking cessation treatment) and correlates of these behaviors (i.e., demographics, attitudinal and systems-related variables).

Results: 43% of the sample did not report making a quit attempt in the last year, but 44% reported making 1-6. 43% and 20%, respectively, reported wanting to quit within the next 6 months or the next 30 days. 61% used a smoking cessation medication during their quit attempt, while 13% utilized counseling. More quit attempts were associated with lower nicotine dependence and carbon monoxide (CO) and greater beliefs about the harms of smoking. Greater quit motivation was associated with lower CO, minority race, benefits of cessation counseling and importance of counseling within the clinic. A greater likelihood of using smoking cessation medications was associated with being female, smoking more cigarettes and receiving smoking cessation advice. A greater likelihood of using smoking cessation counseling was associated with being male, greater academic achievement and receiving smoking cessation advice.

Conclusions: Many smokers with SMI are engaged in efforts to quit smoking. Measures of smoking cessation behavior are associated with tobacco use indicators, beliefs about smoking, race and gender, and receiving cessation advice.

Implications: Consideration of factors related to cessation behaviors among smokers with serious mental illness continues to be warranted, due to their high smoking rates compared to the general population. Increasing our understanding of these predictive characteristics can help promote higher engagement in evidence-based smoking cessation treatments among this sub-population.