Predictors of smoking cessation group treatment engagement among veterans with serious mental illness

Abstract

High prevalence rates of tobacco use, particularly cigarettes, pose a serious health threat for individuals with serious mental illness (SMI), and research has demonstrated the effectiveness of pharmacotherapy and psychosocial interventions to reduce tobacco use in this group. However, few studies have considered predictors of tobacco cessation treatment engagement among individuals with SMI. The current study examined predictors of engagement in smoking cessation groups among veterans with SMI engaged in mental health services at three VA medical centers. All veterans were participating in a smoking cessation treatment study. Of 178 veterans who completed baseline assessments, 127 (83.6%) engaged in treatment, defined as attending at least three group sessions. Forty-one (N = 41) predictors across five domains (demographics, psychiatric concerns, medical concerns, smoking history, and self-efficacy to quit smoking) were identified based on previous research and clinical expertise. Using backward elimination to determine a final multivariable logistic regression model, three predictors were found to be significantly related to treatment engagement: marital status (never-married individuals more likely to engage); previous engagement in group smoking cessation services; and greater severity of positive symptoms on the Brief Psychiatric Rating Scale. When included in the multivariable logistic regression model, the full model discriminates between engagers and non-engagers reasonably well (c statistic = 0.73). Major considerations based on these findings are: individuals with SMI appear to be interested in smoking cessation services; and serious psychiatric symptomatology should not discourage treatment providers from encouraging engagement in smoking cessation services.

Perceived Knowledge as [Protective] Power: Parents’ Protective Efficacy, Information-Seeking, and Scrutiny during COVID-19

“…As one of the most powerful predictors of behavior (Rimal & Adkins, 2003), self-efficacy (Bandura, 1997) has demonstrated broad utility in health communication models and research in predicting a range of health behaviors (Bartle & Harvey, 2017;Lee & Park, 2016;Loton & Waters, 2017;Thrasher et al, 2016;Travaglini et al, 2017). This study extends that work into a new domain and proposes the construct of protective efficacy, which shifts the behavioral focus from the self to a dependent other.…”

“…Self-efficacy is operationalized as the individual assessment of behavioral and cognitive ability to perform a goal behavior or complete a task. As one of the most powerful predictors of human behavior (Rimal & Adkins, 2003), self-efficacy has been used to understand health behaviors such as smoking cessation (Thrasher et al, 2016;Travaglini et al, 2017), infant feeding (Bartle & Harvey, 2017), psychological distress (Loton & Waters, 2017), fruit consumption (Leung et al, 2017), indoor tanning (Mays & Evans, 2017), and pandemic flu (Lee & Park, 2016).…”

Predicting Engagement in Smoking Cessation Treatment Following a Brief Telephone Evaluation and Referral Session

“…Few if any prior studies have examined whether particular psychiatric diagnoses influence smoking cessation treatment engagement. However, a study of engagement among smokers with serious mental illness found those with more severe symptoms were less likely to attend treatment (Travaglini, Li, Brown, Bennett, 2017).…”

Remission from nicotine dependence among people with severe mental illness who received help/services for tobacco/nicotine use

“…Previous research conducted on the general and psychiatric populations has found several factors associated with the effectiveness of and engagement in tobacco/nicotine cessation efforts. Treatment engagement is positively associated with older age (Cupertino et al, 2007; Khara, Okoli, Nagarajan, Aziz, & Hanley, 2015; Richards et al, 2014), higher education (Cupertino et al, 2007), healthcare coverage (Cupertino et al, 2007; Richards et al, 2014), unemployment (Lee, Hayes, McQuaid, & Borrelli, 2010), severity of mental illness‐related symptoms (Lee et al, 2010; MacPherson, Stipelman, Duplinsky, Brown, & Lejuez, 2008; Richards et al, 2014); history of substance use (Richards et al, 2014); general health (Khara et al, 2015); previous smoking treatment use (Travaglini, Li, Brown, & Bennett, 2017); and late onset of smoking (Aschbrenner, Ferron, Mueser, Bartels, & Brunette, 2015; Khara et al, 2015; Lee et al, 2010; Trainor & Leavey, 2016; Travaglini et al, 2017). These other potential factors (e.g., comorbidity with another mental illness) should be taken into consideration when examining and comparing the probability of remission from nicotine dependence among people with SMI by type of help/services received for tobacco/nicotine use.…”